Lexical Sentiment Analysis in Slovenian Texts

OpenAIRE

VOLČANŠEK, MATEJA

2015-01-01

The goal of this thesis is to create a sentiment dictionary for the Slovenian language which can be used in lexical methods for automatic sentiment analysis. We start from a sentiment dictionary for the English language, translate it semi-automatically to Slovenian and curate its content. We test the performance of using the translated dictionary for automated lexical sentiment analysis on a corpus of 5000 manually annotated Slovenian news articles gathered from the main Slovenian news por...

Revolutionary Sentiment in Slave Narratives

DEFF Research Database (Denmark)

Simonsen, Karen-Margrethe

2016-01-01

of genre and are written not by the victims but by ‘spectators’, political or human rights agents, historians or literary writers who are in a distanced position from the actual slavery. In order to understand the role of sentimentalism in slave narratives, I will discuss the sentimental novel by Gertrudis...... Gómez de Avellaneda: Sab (the Cuban/Spanish equivalent of Uncle Tom’s Cabin), written between 1836 and 1839 and published 1841 in Spain. I will argue that the sentimentalism of Sab is of a revolutionary kind, based in a conception of natural law and that its aim is a radical transformation of social...... hierarchies. The paper will be divided into three parts: 1. First I will discuss what sentimentalism is and its relation to politics and especially abolitionism in the 19th century. 2. Then I will analyze Sab’s genre trying to establish the different functions of sentimentality, discussing the tragic modes...

On Three Defenses of Sentimentalism

OpenAIRE

Iwasa, Noriaki

2013-01-01

This essay shows that a moral sense or moral sentiments alone cannot identify appropriate morals. To this end, the essay analyzes three defenses of Francis Hutcheson’s, David Hume’s, and Adam Smith’s moral sense theories against the relativism charge that a moral sense or moral sentiments vary across people, societies, cultures, or times. The first defense is the claim that there is a universal moral sense or universal moral sentiments. However, even if they exist, a moral sense or moral sent...

Is humility a sentiment?

Science.gov (United States)

Weidman, Aaron C; Tracy, Jessica L

2017-01-01

Gervais & Fessler reintroduce the concept of a sentiment as a framework for conceptualizing contempt, a construct with both attitudinal and emotional components. We propose that humility might also fit this mold. We review recent findings regarding the antecedents, phenomenology, and functional consequences of humility, and discuss why conceptualizing it as a sentiment may advance our understanding of this construct.

Sentiment Analysis and Opinion Mining

CERN Document Server

Liu, Bing

2012-01-01

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions

Qualitative and Quantitative Sentiment Proxies

DEFF Research Database (Denmark)

Zhao, Zeyan; Ahmad, Khurshid

2015-01-01

Sentiment analysis is a content-analytic investigative framework for researchers, traders and the general public involved in financial markets. This analysis is based on carefully sourced and elaborately constructed proxies for market sentiment and has emerged as a basis for analysing movements...

Using Tweets for Assigning Sentiments to Regions

NARCIS (Netherlands)

Tjong Kim Sang, Erik

2014-01-01

We derive a sentiment lexicon for Dutch tweets and apply the lexicon for classifying Dutch tweets as positive, negative or neutral. The classifier enables us to test what regions in the Netherlands and Flanders express more positive sentiment on Twitter than others. The results reveal sentiment

Sentiment classification technology based on Markov logic networks

Science.gov (United States)

He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

2016-07-01

With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

Naturalizing sentimentalism for environmental ethics

DEFF Research Database (Denmark)

Kasperbauer, Tyler Joshua

2015-01-01

. One way of testing the empirical adequacy of sentimentalism is by looking at research on environmental values. A classic problem in environmental ethics is providing an account of the intrinsic value of nonhuman entities, which is often thought to be inconsistent with sentimentalism. However...

Social media sentiment and consumer confidence

OpenAIRE

Daas, Piet J.H.; Puts, Marco J.H.

2014-01-01

Changes in the sentiment of Dutch public social media messages were compared with changes in monthly consumer confidence over a period of three-and-a-half years, revealing that both were highly correlated (up to r = 0.9) and that both series cointegrated. This phenomenon is predominantly affected by changes in the sentiment of all Dutch public Facebook messages. The inclusion of various selections of public Twitter messages improved this association and the response to changes in sentiment. G...

Maintaining Sentiment Polarity in Translation of User-Generated Content

Directory of Open Access Journals (Sweden)

Lohar Pintu

2017-06-01

Full Text Available The advent of social media has shaken the very foundations of how we share information, with Twitter, Facebook, and Linkedin among many well-known social networking platforms that facilitate information generation and distribution. However, the maximum 140-character restriction in Twitter encourages users to (sometimes deliberately write somewhat informally in most cases. As a result, machine translation (MT of user-generated content (UGC becomes much more difficult for such noisy texts. In addition to translation quality being affected, this phenomenon may also negatively impact sentiment preservation in the translation process. That is, a sentence with positive sentiment in the source language may be translated into a sentence with negative or neutral sentiment in the target language. In this paper, we analyse both sentiment preservation and MT quality per se in the context of UGC, focusing especially on whether sentiment classification helps improve sentiment preservation in MT of UGC. We build four different experimental setups for tweet translation (i using a single MT model trained on the whole Twitter parallel corpus, (ii using multiple MT models based on sentiment classification, (iii using MT models including additional out-of-domain data, and (iv adding MT models based on the phrase-table fill-up method to accompany the sentiment translation models with an aim of improving MT quality and at the same time maintaining sentiment polarity preservation. Our empirical evaluation shows that despite a slight deterioration in MT quality, our system significantly outperforms the Baseline MT system (without using sentiment classification in terms of sentiment preservation. We also demonstrate that using an MT engine that conveys a sentiment different from that of the UGC can even worsen both the translation quality and sentiment preservation.

Weibo sentiments and stock return: A time-frequency view.

Science.gov (United States)

Xu, Yingying; Liu, Zhixin; Zhao, Jichang; Su, Chiwei

2017-01-01

This study provides new insights into the relationships between social media sentiments and the stock market in China. Based on machine learning, we classify microblogs posted on Sina Weibo, a Twitter's variant in China into five detailed sentiments of anger, disgust, fear, joy, and sadness. Using wavelet analysis, we find close positive linkages between sentiments and the stock return, which have both frequency and time-varying features. Five detailed sentiments are positively related to the stock return for certain periods, particularly since October 2014 at medium to high frequencies of less than ten trading days, when the stock return is undergoing significant fluctuations. Sadness appears to have a closer relationship with the stock return than the other four sentiments. As to the lead-lag relationships, the stock return causes Weibo sentiments rather than reverse for most of the periods with significant linkages. Compared with polarity sentiments (negative vs. positive), detailed sentiments provide more information regarding relationships between Weibo sentiments and the stock market. The stock market exerts positive effects on bullishness and agreement of microblogs. Meanwhile, agreement leads the stock return in-phase at the frequency of approximately 40 trading days, indicating that less disagreement improves certainty about the stock market.

Weibo sentiments and stock return: A time-frequency view.

Directory of Open Access Journals (Sweden)

Yingying Xu

Full Text Available This study provides new insights into the relationships between social media sentiments and the stock market in China. Based on machine learning, we classify microblogs posted on Sina Weibo, a Twitter's variant in China into five detailed sentiments of anger, disgust, fear, joy, and sadness. Using wavelet analysis, we find close positive linkages between sentiments and the stock return, which have both frequency and time-varying features. Five detailed sentiments are positively related to the stock return for certain periods, particularly since October 2014 at medium to high frequencies of less than ten trading days, when the stock return is undergoing significant fluctuations. Sadness appears to have a closer relationship with the stock return than the other four sentiments. As to the lead-lag relationships, the stock return causes Weibo sentiments rather than reverse for most of the periods with significant linkages. Compared with polarity sentiments (negative vs. positive, detailed sentiments provide more information regarding relationships between Weibo sentiments and the stock market. The stock market exerts positive effects on bullishness and agreement of microblogs. Meanwhile, agreement leads the stock return in-phase at the frequency of approximately 40 trading days, indicating that less disagreement improves certainty about the stock market.

Weibo sentiments and stock return: A time-frequency view

Science.gov (United States)

Liu, Zhixin; Zhao, Jichang; Su, Chiwei

2017-01-01

This study provides new insights into the relationships between social media sentiments and the stock market in China. Based on machine learning, we classify microblogs posted on Sina Weibo, a Twitter’s variant in China into five detailed sentiments of anger, disgust, fear, joy, and sadness. Using wavelet analysis, we find close positive linkages between sentiments and the stock return, which have both frequency and time-varying features. Five detailed sentiments are positively related to the stock return for certain periods, particularly since October 2014 at medium to high frequencies of less than ten trading days, when the stock return is undergoing significant fluctuations. Sadness appears to have a closer relationship with the stock return than the other four sentiments. As to the lead-lag relationships, the stock return causes Weibo sentiments rather than reverse for most of the periods with significant linkages. Compared with polarity sentiments (negative vs. positive), detailed sentiments provide more information regarding relationships between Weibo sentiments and the stock market. The stock market exerts positive effects on bullishness and agreement of microblogs. Meanwhile, agreement leads the stock return in-phase at the frequency of approximately 40 trading days, indicating that less disagreement improves certainty about the stock market. PMID:28672026

A Peculiar Sentiment Analysis Advancement in Big Data

Science.gov (United States)

Valera, Manisha; Patel, Yash

2018-01-01

Every company wants to discover what its customers feel about it. But sentiment analysis can get coarser and turn inward to improve employee as well as customers’ satisfaction. A term called sentiment analysis, or the mathematical taxonomy of statements’ negative or positive connotations, gives companies potent ways to analyse cumulative language data across all sorts of communications. There’s real value in measuring sentiment inside and outside your company. Our big data experts analyse the core grounds of the problems raised while handling giant datasets and find solutions to efficiently manage massive datasets with ease. We built a sentiment analysis solution to measure positive and negative sentiments with top rating products for Amazon.com‘s Electronics products as against competitor products.

Network public opinion space sentiment tendency analyze based on recurrent convolution neural network

Science.gov (United States)

Zhang, Gaowei; Xu, Lingyu; Wang, Lei

2018-04-01

The purpose of this chapter is to analyze the investor's psychological characteristics and investment decision-making behavior characteristics, to study the investor sentiment under the network public opinion, and then analyze from three aspects: First, investor sentiment analysis and how to spread in the online media; The influence mechanism of investor's emotion on the stock market and its effect; the third one is to measure the investor's emotion based on the degree of attention, trying hard to sort out the internal relations between the investor's sentiment and the network public opinion and the stock market, in order to lay the theoretical foundation of this article.

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words.

Science.gov (United States)

Wang, Bingkun; Huang, Yongfeng; Wu, Xian; Li, Xing

2015-01-01

With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods.

A New Index of Housing Sentiment

DEFF Research Database (Denmark)

Bork, Lasse; Møller, Stig Vinther; Pedersen, Thomas Quistgaard

We propose a new measure for housing sentiment and show that it accurately tracks expectations about future house price growth rates. We construct the housing sentiment index using partial least squares on questions related to consumers' opinions of buying conditions for houses from University...

A New Index of Housing Sentiment

DEFF Research Database (Denmark)

Bork, Lasse; Møller, Stig Vinther; Pedersen, Thomas Quistgaard

We propose a new measure for housing sentiment and show that it accurately tracks expectations about future house price growth rates. We construct the housing sentiment index using partial least squares on household survey responses to questions about buying conditions for houses. We …find...

Sentiment Polarization and Balance among Users in Online Social Networks

DEFF Research Database (Denmark)

Hillmann, Robert; Trier, Matthias

2012-01-01

Communication within online social network applications enables users to express and share sentiments electronically. Existing studies examined the existence or distribution of sentiments in online communication at a general level or in small-observed groups. Our paper extends this research...... by analyzing sentiment exchange within social networks from an ego-network perspective. We draw from research on social influence and social attachment to develop theories of node polarization, balance effects and sentiment mirroring within communication dyads. Our empirical analysis covers a multitude...... of social networks in which the sentiment valence of all messages was determined. Subsequently we studied ego-networks of focal actors (ego) and their immediate contacts. Results support our theories and indicate that actors develop polarized sentiments towards individual peers but keep sentiment in balance...

Investor’s Sentiments and Stock Market Volatility: an empirical evidence from emerging stock market

Directory of Open Access Journals (Sweden)

Mobeen Ur Rehman

2013-05-01

Full Text Available The concept of efficient market hypothesis has prevailed the financial markets for a long time which says that the prices of the securities reflect all available information. This approach was mainly followed by the rational investors but with the passage of time, the concept of behavioral finance emerged due to some of the major global financial crashes. This concept states that there are investors trading in the market making decisions on the basis of sentiments not on any fundamental information. Such class of traders is called the noise traders and they are mainly responsible for any disruption in the returns of the securities. In this paper we will try to find whether these sentiments of the investors affect the returns of the securities listed on the Karachi stock exchange. We will use the investor sentiment index that uses the six proxies the data on which has been collected mainly from the Karachi stock exchange. Volatility of the stock market returns will be calculated and regressed with the sentimental equation discussed above as the independent variable. This study will help us to find out the extent to which these sentiments influence the stock market returns in weak form efficient market and also it will help us to identify the presence of such irrational noise traders in our financial market.

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

Directory of Open Access Journals (Sweden)

Bingkun Wang

2015-01-01

Full Text Available With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods.

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words

Science.gov (United States)

Huang, Yongfeng; Wu, Xian; Li, Xing

2015-01-01

With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive and negative polarity are quite instrumental for sentiment analysis. However, most of the existing methods for identifying polarity of sentiment words only consider the positive and negative polarity by the Cantor set, and no attention is paid to the fuzziness of the polarity intensity of sentiment words. In order to improve the performance, we propose a fuzzy computing model to identify the polarity of Chinese sentiment words in this paper. There are three major contributions in this paper. Firstly, we propose a method to compute polarity intensity of sentiment morphemes and sentiment words. Secondly, we construct a fuzzy sentiment classifier and propose two different methods to compute the parameter of the fuzzy classifier. Thirdly, we conduct extensive experiments on four sentiment words datasets and three review datasets, and the experimental results indicate that our model performs better than the state-of-the-art methods. PMID:26106409

Building an Arabic Sentiment Lexicon Using Semi-supervised Learning

Directory of Open Access Journals (Sweden)

Fawaz H.H. Mahyoub

2014-12-01

Full Text Available Sentiment analysis is the process of determining a predefined sentiment from text written in a natural language with respect to the entity to which it is referring. A number of lexical resources are available to facilitate this task in English. One such resource is the SentiWordNet, which assigns sentiment scores to words found in the English WordNet. In this paper, we present an Arabic sentiment lexicon that assigns sentiment scores to the words found in the Arabic WordNet. Starting from a small seed list of positive and negative words, we used semi-supervised learning to propagate the scores in the Arabic WordNet by exploiting the synset relations. Our algorithm assigned a positive sentiment score to more than 800, a negative score to more than 600 and a neutral score to more than 6000 words in the Arabic WordNet. The lexicon was evaluated by incorporating it into a machine learning-based classifier. The experiments were conducted on several Arabic sentiment corpora, and we were able to achieve a 96% classification accuracy.

Topic Modeling in Sentiment Analysis: A Systematic Review

Directory of Open Access Journals (Sweden)

Toqir Ahmad Rana

2016-06-01

Full Text Available With the expansion and acceptance of Word Wide Web, sentiment analysis has become progressively popular research area in information retrieval and web data analysis. Due to the huge amount of user-generated contents over blogs, forums, social media, etc., sentiment analysis has attracted researchers both in academia and industry, since it deals with the extraction of opinions and sentiments. In this paper, we have presented a review of topic modeling, especially LDA-based techniques, in sentiment analysis. We have presented a detailed analysis of diverse approaches and techniques, and compared the accuracy of different systems among them. The results of different approaches have been summarized, analyzed and presented in a sophisticated fashion. This is the really effort to explore different topic modeling techniques in the capacity of sentiment analysis and imparting a comprehensive comparison among them.

Sentiment Analysis Based on Psychological and Linguistic Features for Spanish Language

KAUST Repository

Salas-Zárate, María Pilar

2017-03-14

Recent research activities in the areas of opinion mining, sentiment analysis and emotion detection from natural language texts are gaining ground under the umbrella of affective computing. Nowadays, there is a huge amount of text data available in the Social Media (e.g. forums, blogs, and social networks) concerning to users’ opinions about experiences buying products and hiring services. Sentiment analysis or opinion mining is the field of study that analyses people’s opinions and mood from written text available on the Web. In this paper, we present extensive experiments to evaluate the effectiveness of the psychological and linguistic features for sentiment classification. To this purpose, we have used four psycholinguistic dimensions obtained from LIWC, and one stylometric dimension obtained from WordSmith, for the subsequent training of the SVM, Naïve Bayes, and J48 algorithms. Also, we create a corpus of tourist reviews from the travel website TripAdvisor. The findings reveal that the stylometric dimension is quite feasible for sentiment classification. Finally, with regard to the classifiers, SVM provides better results than Naïve Bayes and J48 with an F-measure rate of 90.8%.

Telkom UData sentiment analysis using crowdsourcing and trust

Science.gov (United States)

Noer, Edvya; Sulistyo Kusumo, Dana; Rusmawati, Yanti

2018-03-01

Microblogging sites have millions of people sharing their thoughts daily because of its characteristic short and simple manner of expression. Sentiments analysis are often being used to analyse the user customer opinions regarding brand images or products. For some reasons, not all sentiment generated using this existing machine-based algorithms yields satisfying results. This is mostly due to the uniformity of the informal language used in the social media sentences. This condition also occurs in Telkom UData on our preliminary study, where the machine-based provided less then optimal results in analysing the sentiment. This research offers concepts with human interaction using crowdsourcing where people are involved to analyse sentiments, while forming the new training dataset at the same time. From the research results found that sarcastic and contradictory sentences can be recognized by humans, to be utilized as new training datasets for further machine learning. From this experiments, that approach are likely increase the accuracy of the sentiments in UData from neutral to become positive or negative polarized up to 39%. We do as well simulated trust concept through sociometric to ensure the crowdsource workers are trusted and capable enough in analysing the sentiments on social media.

Anti-cyclic regulation of the Ukrainian economy under current conditions of the international markets volatility

Directory of Open Access Journals (Sweden)

Volodymyr Satsyk

2009-04-01

Full Text Available In the article there are considered the theoretical and methodological basis of anti-cyclic regulation of the countries’ economy under conditions of the world economy globalization. It suggests the analysis of practices of implementing of anti-cyclic policy in highly developed states, its defining features and directions under current global financial and economic crisis. There has been researched a practical toolkit of economic cycles diagnostics and cyclic fluctuations of total business activity in Ukraine based on this study. There are suggested recommendations concerning the formation of the effective mechanism of anti-cyclic regulation of the Ukrainian economy.

Anti-Globalization or Alter-Globalization? Mapping the Political Ideology of the Global Justice Movement

NARCIS (Netherlands)

B. Steger, Manfred; Wilson, E.K.

Steger, Manfred B. and Erin K. Wilson. (2012) Anti-Globalization or Alter-Globalization? Mapping the Political Ideology of the Global Justice Movement. International Studies Quarterly, doi: 10.1111/j.1468-2478.2012.00740.x?(c) 2012 International Studies Association Globalization has unsettled

Sentiment analysis on tweets for social events

DEFF Research Database (Denmark)

Zhou, Xujuan; Tao, Xiaohui; Yong, Jianming

2013-01-01

Sentiment analysis or opinion mining is an important type of text analysis that aims to support decision making by extracting and analyzing opinion oriented text, identifying positive and negative opinions, and measuring how positively or negatively an entity (i.e., people, organization, event......, location, product, topic, etc.) is regarded. As more and more users express their political and religious views on Twitter, tweets become valuable sources of people's opinions. Tweets data can be efficiently used to infer people's opinions for marketing or social studies. This paper proposes a Tweets...... Sentiment Analysis Model (TSAM) that can spot the societal interest and general people's opinions in regard to a social event. In this paper, Australian federal election 2010 event was taken as an example for sentiment analysis experiments. We are primarily interested in the sentiment of the specific...

Wealth dynamics in a sentiment-driven market

Science.gov (United States)

Goykhman, Mikhail

2017-12-01

We study dynamics of a simulated world with stock and money, driven by the externally given processes which we refer to as sentiments. The considered sentiments influence the buy/sell stock trading attitude, the perceived price uncertainty, and the trading intensity of all or a part of the market participants. We study how the wealth of market participants evolves in time in such an environment. We discuss the opposite perspective in which the parameters of the sentiment processes can be inferred a posteriori from the observed market behavior.

ARCHITECTURE OF A SENTIMENT ANALYSIS PLATFORM

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CRISTIAN BUCUR

2015-06-01

Full Text Available A new domain of research evolved in the last decade, called sentiment analysis that tries to extract knowledge from opinionated text documents. The article presents an overview of the domain and present an architecture of a system that could perform sentiment analysis processes. Based on previous researches are presented two methods for performing classification and the results obtained.

Sentiment analysis and ontology engineering an environment of computational intelligence

CERN Document Server

Chen, Shyi-Ming

2016-01-01

This edited volume provides the reader with a fully updated, in-depth treatise on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of models of sentiment analysis and ontology –oriented engineering. The volume involves studies devoted to key issues of sentiment analysis, sentiment models, and ontology engineering. The book is structured into three main parts. The first part offers a comprehensive and prudently structured exposure to the fundamentals of sentiment analysis and natural language processing. The second part consists of studies devoted to the concepts, methodologies, and algorithmic developments elaborating on fuzzy linguistic aggregation to emotion analysis, carrying out interpretability of computational sentiment models, emotion classification, sentiment-oriented information retrieval, a methodology of adaptive dynamics in knowledge acquisition. The third part includes a plethora of applica...

An effective convolutional neural network model for Chinese sentiment analysis

Science.gov (United States)

Zhang, Yu; Chen, Mengdong; Liu, Lianzhong; Wang, Yadong

2017-06-01

Nowadays microblog is getting more and more popular. People are increasingly accustomed to expressing their opinions on Twitter, Facebook and Sina Weibo. Sentiment analysis of microblog has received significant attention, both in academia and in industry. So far, Chinese microblog exploration still needs lots of further work. In recent years CNN has also been used to deal with NLP tasks, and already achieved good results. However, these methods ignore the effective use of a large number of existing sentimental resources. For this purpose, we propose a Lexicon-based Sentiment Convolutional Neural Networks (LSCNN) model focus on Weibo's sentiment analysis, which combines two CNNs, trained individually base on sentiment features and word embedding, at the fully connected hidden layer. The experimental results show that our model outperforms the CNN model only with word embedding features on microblog sentiment analysis task.

A Sentiment Delivering Estimate Scheme Based on Trust Chain in Mobile Social Network

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Meizi Li

2015-01-01

Full Text Available User sentiment analysis has become a flourishing frontier in data mining mobile social network platform since the mobile social network plays a significant role in users’ daily communication and sentiment interaction. This study studies the scheme of sentiment estimate by using the users’ trustworthy relationships for evaluating sentiment delivering. First, we address an overview of sentiment delivering estimate scheme and propose its related definitions, that is, trust chain among users, sentiment semantics, and sentiment ontology. Second, this study proposes the trust chain model and its evaluation method, which is composed of evaluation of atomic, serial, parallel, and combined trust chains. Then, we propose sentiment modeling method by presenting its modeling rules. Further, we propose the sentiment delivering estimate scheme from two aspects: explicit and implicit sentiment delivering estimate schemes, based on trust chain and sentiment modeling method. Finally, examinations and results are given to further explain effectiveness and feasibility of our scheme.

Sentiment analysis enhancement with target variable in Kumar’s Algorithm

Science.gov (United States)

Arman, A. A.; Kawi, A. B.; Hurriyati, R.

2016-04-01

Sentiment analysis (also known as opinion mining) refers to the use of text analysis and computational linguistics to identify and extract subjective information in source materials. Sentiment analysis is widely applied to reviews discussion that is being talked in social media for many purposes, ranging from marketing, customer service, or public opinion of public policy. One of the popular algorithm for Sentiment Analysis implementation is Kumar algorithm that developed by Kumar and Sebastian. Kumar algorithm can identify the sentiment score of the statement, sentence or tweet, but cannot determine the relationship of the object or target related to the sentiment being analysed. This research proposed solution for that challenge by adding additional component that represent object or target to the existing algorithm (Kumar algorithm). The result of this research is a modified algorithm that can give sentiment score based on a given object or target.

Influence and Dissemination Of Sentiments in Social Network Communication Patterns

DEFF Research Database (Denmark)

Hillmann, Robert; Trier, Matthias

2013-01-01

Previous research suggests the existence of sentiments in online social networks. In comparison to real life human interaction, in which sentiments have been shown to have an influence on human behaviour, it is not yet completely understood which mechanisms explain how sentiments influence users ...... that express the same sentiment polarization. We interpret these findings and suggest future research to advance our currently limited theories that assume perceived and generalized social influence to path-dependent social influence models that consider actual behaviour....

Quantifying Sentiment and Influence in Blogspaces

Energy Technology Data Exchange (ETDEWEB)

Hui, Peter SY; Gregory, Michelle L.

2010-07-25

The weblog, or blog, has become a popular form of social media, through which authors can write posts, which can in turn generate feedback in the form of user comments. When considered in totality, a collection of blogs can thus be viewed as a sort of informal collection of mass sentiment and opinion. An obvious topic of interest might be to mine this collection to obtain some gauge of public sentiment over the wide variety of topics contained therein. However, the sheer size of the so-called blogosphere, combined with the fact that the subjects of posts can vary over a practically limitless number of topics poses some serious challenges when any meaningful analysis is attempted. Namely, the fact that largely anyone with access to the Internet can author their own blog, raises the serious issue of credibility— should some blogs be considered to be more influential than others, and consequently, when gauging sentiment with respect to a topic, should some blogs be weighted more heavily than others? In addition, as new posts and comments can be made on almost a constant basis, any blog analysis algorithm must be able to handle such updates efficiently. In this paper, we give a formalization of the blog model. We give formal methods of quantifying sentiment and influence with respect to a hierarchy of topics, with the specific aim of facilitating the computation of a per-topic, influence-weighted sentiment measure. Finally, as efficiency is a specific endgoal, we give upper bounds on the time required to update these values with new posts, showing that our analysis and algorithms are scalable.

Lexicon-based sentient analysis by mapping conveyed sentiment to intended sentiment

NARCIS (Netherlands)

Hogenboom, A.; Bal, M.; Frasincar, F.; Bal, D.; Kaymak, U.; De Jong, F.

2014-01-01

As consumers nowadays generate increasingly more content describing their experiences with, e.g., products and brands in various languages, information systems monitoring a universal, language-independent measure of peoples intended sentiment are crucial for todays businesses. In order to facilitate

Beyond “Peak Car”: A reflection on the evolution of public sentiment about the role of cars in cities

Directory of Open Access Journals (Sweden)

Martin E.H. Lee-Gosselin

2017-03-01

Full Text Available In this volume, Jones has made a persuasive case for considering recently observed reductions in car use (and sometimes car ownership in a number of major northern cities as part of an evolutionary process, rather than the consequence of transient conditions such as the economic downturn of 2008 and its relatively slow recovery. In an era bringing new service models for mobility and communications that have important implications for safety, security, the environment and well-being, he points to the role of public attitudes and sentiments that may underlie changing policy priorities and an associated culture change with respect to transport in cities and the reclamation of street space. This paper briefly explores the role of public sentiments and reflects on the apparent emergence of a popular subculture that favors living, if possible, without owning or using cars, in contrast to older subcultures embracing more extreme sentiments that are either Car-centered or emphatically anti-car.

Towards sentiment analysis application in housing projects

Science.gov (United States)

Mahadzir, Nurul Husna; Omar, Mohd Faizal; Nawi, Mohd Nasrun Mohd

2016-08-01

In becoming a develop nation by 2020, Malaysia Government realized the need in providing affordable house to the public. Since Second Malaysia Plan, government has implemented various affordable housing projects and it continues until recent Malaysia Plan. To measure the effectiveness of the initiatives taken, public opinion is necessary. A social media platform has been seen as the most effective mechanism to get information on people's thought and feeling towards certain issues. One of the best ways to extract emotions and thoughts from what people post in social media is through Sentiment Analysis (SA). There are three different levels of analysis: document level, sentence level and feature level. Most of previous research focused on the classification of sentiment at document or sentence level. Unfortunately, both document and sentence level does not discover what exactly people like or not. While the analysis based on feature, there exist accuracy problem when classifying the sentiment scores. This paper will propose a new framework that focuses on sentiment classification scores at feature level to overcome the uncertainty and accuracy issues on the result.

Climate Change, Disaster and Sentiment Analysis over Social Media Mining

Science.gov (United States)

Lee, J.; McCusker, J. P.; McGuinness, D. L.

2012-12-01

Accelerated climate change causes disasters and disrupts people living all over the globe. Disruptive climate events are often reflected in expressed sentiments of the people affected. Monitoring changes in these sentiments during and after disasters can reveal relationships between climate change and mental health. We developed a semantic web tool that uses linked data principles and semantic web technologies to integrate data from multiple sources and analyze them together. We are converting statistical data on climate change and disaster records obtained from the World Bank data catalog and the International Disaster Database into a Resource Description Framework (RDF) representation that was annotated with the RDF Data Cube vocabulary. We compare these data with a dataset of tweets that mention terms from the Emotion Ontology to get a sense of how disasters can impact the affected populations. This dataset is being gathered using an infrastructure we developed that extracts term uses in Twitter with controlled vocabularies. This data was also converted to RDF structure so that statistical data on the climate change and disasters is analyzed together with sentiment data. To visualize and explore relationship of the multiple data across the dimensions of time and location, we use the qb.js framework. We are using this approach to investigate the social and emotional impact of climate change. We hope that this will demonstrate the use of social media data as a valuable source of understanding on global climate change.

Sentiments and Perceptions of Business Respondents on Social Media: an Exploratory Analysis

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Torres van Grinsven Vanessa

2015-06-01

Full Text Available The perceptions and sentiments of business respondents are considered important for statistical bureaus. As perceptions and sentiments are related to the behavior of the people expressing them, gaining insights into the perceptions and sentiments of business respondents is of interest to understand business survey response. In this article we present an exploratory analysis of expressions in the social media regarding Statistics Netherlands. In recent years, social media have become an important infrastructure for communication flows and thus an essential network in our social structure. Within that network participants are actively involved in expressing sentiments and perceptions. The results of our analysis provide insights into the perceptions and sentiments that business respondents have of this national statistical institute and specifically its business surveys. They point towards the specific causes that have led to a positive or a negative sentiment. Based on these results, recommendations aimed at influencing the perceptions and sentiments will be discussed, with the ultimate goal of stimulating survey participation. We also suggest recommendations regarding social media studies on sentiments and perceptions of survey respondents.

Determining negation scope and strength in sentiment analysis

NARCIS (Netherlands)

Hogenboom, A.C.; Iterson, van P.; Heerschop, B.M.W.T.; Frasincar, F.; Kaymak, U.

2011-01-01

A key element for decision makers to track is their stakeholders' sentiment. Recent developments show a tendency of including various aspects other than word frequencies in automated sentiment analysis approaches. One of these aspects is negation, which can be accounted for in various ways. We

Sentiment Diffusion of Public Opinions about Hot Events: Based on Complex Network.

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Xiaoqing Hao

Full Text Available To study the sentiment diffusion of online public opinions about hot events, we collected people's posts through web data mining techniques. We calculated the sentiment value of each post based on a sentiment dictionary. Next, we divided those posts into five different orientations of sentiments: strongly positive (P, weakly positive (p, neutral (o, weakly negative (n, and strongly negative (N. These sentiments are combined into modes through coarse graining. We constructed sentiment mode complex network of online public opinions (SMCOP with modes as nodes and the conversion relation in chronological order between different types of modes as edges. We calculated the strength, k-plex clique, clustering coefficient and betweenness centrality of the SMCOP. The results show that the strength distribution obeys power law. Most posts' sentiments are weakly positive and neutral, whereas few are strongly negative. There are weakly positive subgroups and neutral subgroups with ppppp and ooooo as the core mode, respectively. Few modes have larger betweenness centrality values and most modes convert to each other with these higher betweenness centrality modes as mediums. Therefore, the relevant person or institutes can take measures to lead people's sentiments regarding online hot events according to the sentiment diffusion mechanism.

Sentiment Analysis of User-Generated Content on Drug Review Websites

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Na, Jin-Cheon

2015-03-01

Full Text Available This study develops an effective method for sentiment analysis of user-generated content on drug review websites, which has not been investigated extensively compared to other general domains, such as product reviews. A clause-level sentiment analysis algorithm is developed since each sentence can contain multiple clauses discussing multiple aspects of a drug. The method adopts a pure linguistic approach of computing the sentiment orientation (positive, negative, or neutral of a clause from the prior sentiment scores assigned to words, taking into consideration the grammatical relations and semantic annotation (such as disorder terms of words in the clause. Experiment results with 2,700 clauses show the effectiveness of the proposed approach, and it performed significantly better than the baseline approaches using a machine learning approach. Various challenging issues were identified and discussed through error analysis. The application of the proposed sentiment analysis approach will be useful not only for patients, but also for drug makers and clinicians to obtain valuable summaries of public opinion. Since sentiment analysis is domain specific, domain knowledge in drug reviews is incorporated into the sentiment analysis algorithm to provide more accurate analysis. In particular, MetaMap is used to map various health and medical terms (such as disease and drug names to semantic types in the Unified Medical Language System (UMLS Semantic Network.

Sentiment analysis of Arabic tweets using text mining techniques

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Al-Horaibi, Lamia; Khan, Muhammad Badruddin

2016-07-01

Sentiment analysis has become a flourishing field of text mining and natural language processing. Sentiment analysis aims to determine whether the text is written to express positive, negative, or neutral emotions about a certain domain. Most sentiment analysis researchers focus on English texts, with very limited resources available for other complex languages, such as Arabic. In this study, the target was to develop an initial model that performs satisfactorily and measures Arabic Twitter sentiment by using machine learning approach, Naïve Bayes and Decision Tree for classification algorithms. The datasets used contains more than 2,000 Arabic tweets collected from Twitter. We performed several experiments to check the performance of the two algorithms classifiers using different combinations of text-processing functions. We found that available facilities for Arabic text processing need to be made from scratch or improved to develop accurate classifiers. The small functionalities developed by us in a Python language environment helped improve the results and proved that sentiment analysis in the Arabic domain needs lot of work on the lexicon side.

Comprehensive Study on Lexicon-based Ensemble Classification Sentiment Analysis

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Łukasz Augustyniak

2015-12-01

Full Text Available We propose a novel method for counting sentiment orientation that outperforms supervised learning approaches in time and memory complexity and is not statistically significantly different from them in accuracy. Our method consists of a novel approach to generating unigram, bigram and trigram lexicons. The proposed method, called frequentiment, is based on calculating the frequency of features (words in the document and averaging their impact on the sentiment score as opposed to documents that do not contain these features. Afterwards, we use ensemble classification to improve the overall accuracy of the method. What is important is that the frequentiment-based lexicons with sentiment threshold selection outperform other popular lexicons and some supervised learners, while being 3–5 times faster than the supervised approach. We compare 37 methods (lexicons, ensembles with lexicon’s predictions as input and supervised learners applied to 10 Amazon review data sets and provide the first statistical comparison of the sentiment annotation methods that include ensemble approaches. It is one of the most comprehensive comparisons of domain sentiment analysis in the literature.

A Video Recall Study of In-session Changes in Sentiment Override.

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Johnson, Lee N; Tambling, Rachel B; Anderson, Shayne R

2015-09-01

This study examines in-session changes in sentiment override over the first three sessions of couple therapy. Couples viewed a video recording of therapy sessions immediately after each of the first three sessions and continuously rated their level of sentiment override. Ninety-eight changes were randomly chosen for analysis. Three talk turns prior to each change was coded using the Family Relational Communication Control Coding System. Results show that changes in sentiment override occur frequently. Repeated incidents of communication control were related to negative change in sentiment override for females. Repeated incidents of being left out of the conversation were related to negative changes in sentiment override for females and positive changes for males. © 2014 Family Process Institute.

Stigmatized ethnicity, public health, and globalization.

Science.gov (United States)

Ali, S Harris

2008-01-01

The prejudicial linking of infection with ethnic minority status has a long-established history, but in some ways this association may have intensified under the contemporary circumstances of the "new public health" and globalization. This study analyzes this conflation of ethnicity and disease victimization by considering the stigmatization process that occurred during the 2003 outbreak of Severe Acute Respiratory Syndrome (SARS) in Toronto. The attribution of stigma during the SARS outbreak occurred in multiple and overlapping ways informed by: (i) the depiction of images of individuals donning respiratory masks; (ii) employment status in the health sector; and (iii) Asian-Canadian and Chinese-Canadian ethnicity. In turn, stigmatization during the SARS crisis facilitated a moral panic of sorts in which racism at a cultural level was expressed and rationalized on the basis of a rhetoric of the new public health and anti-globalization sentiments. With the former, an emphasis on individualized self-protection, in the health sense, justified the generalized avoidance of those stigmatized. In relation to the latter, in the post-9/11 era, avoidance of the stigmatized other was legitimized on the basis of perceiving the SARS threat as a consequence of the mixing of different people predicated by economic and cultural globalization.

EFFECT OF INVESTOR SENTIMENT ON FUTURE RETURNS IN THE NIGERIAN STOCK MARKET

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Udoka Bernard Alajekwu

2017-06-01

Full Text Available The study examined the effect of investor sentiment on future returns in the Nigerian stock market. The OLS regression and granger causality techniques were employed for data analyses. The results showed that (1 investor sentiment has a significant positive effect on stock market returns even after control for fundamentals such as Industrial production index, consumer price index and Treasury bill rate; (2 there is a uni-directional causality that runs from change in investor sentiment (ΔCCI to stock market returns (Rm. Derived finding showed that the inclusion of fundamentals increased the explanatory power of investor sentiment from 3.96% to 33.05%, though at both level, investor sentiment (ΔCCI has low explanatory power on stock market returns. The study posits existence of a dynamic relationship between investor sentiment and the behaviour of stock future returns in Nigeria such that higher sentiment concurrently leads to higher stock prices.

Anti-money laundering: the conditions for global governance and harmonisation

OpenAIRE

Oliveira, Inês Sofia de; Correia, Ines Sofia De Oliveira Gomes De Pinho

2015-01-01

This thesis advances global governance literature by focusing on the conditions under which procedural harmonisation occurs and how it is characterised. It suggests that the existence of a network of intergovernmental organisations (IGOs) complements great powers’ action and acts as a force for harmonisation in the making of international anti-money laundering (AML) standards. Procedural harmonisation is identified firstly, through a discussion on great power coalitions and ...

How global brands compete.

Science.gov (United States)

Holt, Douglas B; Quelch, John A; Taylor, Earl L

2004-09-01

It's time to rethink global branding. More than two decades ago, Harvard Business School professor Theodore Levitt argued that corporations should grow by selling standardized products all over the world. But consumers in most countries had trouble relating to generic products, so executives instead strove for global scale on backstage activities such as production while customizing product features and selling techniques to local tastes. Such "glocal" strategies now rule marketing. Global branding has lost more luster recently because transnational companies have been under siege, with brands like Coca-Cola and Nike becoming lightning rods for antiglobalization protests. The instinctive reaction of most transnational companies has been to try to fly below the radar. But global brands can't escape notice. In fact, most transnational corporations don't realize that because of their power and pervasiveness, people view them differently than they do other firms. In a research project involving 3,300 consumers in 41 countries, the authors found that most people choose one global brand over another because of differences in the brands'global qualities. Ratherthan ignore the global characteristics of their brands, firms must learn to manage those characteristics. That's critical, because future growth for most companies will likely come from foreign markets. Consumers base preferences on three dimensions of global brands--quality (signaled by a company's global stature); the cultural myths that brands author; and firms' efforts to address social problems. The authors also found that it didn't matter to consumers whether the brands they bought were American--a remarkable finding considering that the study was conducted when anti-American sentiment in many nations was on the rise.

Using Social Media Sentiment Analysis for Interaction Design Choices

DEFF Research Database (Denmark)

McGuire, Mark; Kampf, Constance Elizabeth

2015-01-01

Social media analytics is an emerging skill for organizations. Currently, developers are exploring ways to create tools for simplifying social media analysis. These tools tend to focus on gathering data, and using systems to make it meaningful. However, we contend that making social media data...... meaningful is by nature a human-computer interaction problem. We examine this problem around the emerging field of sentiment analysis, exploring criteria for designing sentiment analysis systems based in Human Computer interaction, HCI. We contend that effective sentiment analysis affects audience analysis...

Identifying Sentiment of Hookah-Related Posts on Twitter

Science.gov (United States)

Ramanujam, Jagannathan; Lerman, Kristina; Chu, Kar-Hai; Boley Cruz, Tess; Unger, Jennifer B

2017-01-01

Background The increasing popularity of hookah (or waterpipe) use in the United States and elsewhere has consequences for public health because it has similar health risks to that of combustible cigarettes. While hookah use rapidly increases in popularity, social media data (Twitter, Instagram) can be used to capture and describe the social and environmental contexts in which individuals use, perceive, discuss, and are marketed this tobacco product. These data may allow people to organically report on their sentiment toward tobacco products like hookah unprimed by a researcher, without instrument bias, and at low costs. Objective This study describes the sentiment of hookah-related posts on Twitter and describes the importance of debiasing Twitter data when attempting to understand attitudes. Methods Hookah-related posts on Twitter (N=986,320) were collected from March 24, 2015, to December 2, 2016. Machine learning models were used to describe sentiment on 20 different emotions and to debias the data so that Twitter posts reflected sentiment of legitimate human users and not of social bots or marketing-oriented accounts that would possibly provide overly positive or overly negative sentiment of hookah. Results From the analytical sample, 352,116 tweets (59.50%) were classified as positive while 177,537 (30.00%) were classified as negative, and 62,139 (10.50%) neutral. Among all positive tweets, 218,312 (62.00%) were classified as highly positive emotions (eg, active, alert, excited, elated, happy, and pleasant), while 133,804 (38.00%) positive tweets were classified as passive positive emotions (eg, contented, serene, calm, relaxed, and subdued). Among all negative tweets, 95,870 (54.00%) were classified as subdued negative emotions (eg, sad, unhappy, depressed, and bored) while the remaining 81,667 (46.00%) negative tweets were classified as highly negative emotions (eg, tense, nervous, stressed, upset, and unpleasant). Sentiment changed drastically when

Using Sentiment Analysis to Observe How Science is Communicated

Science.gov (United States)

Topping, David; Illingworth, Sam

2016-04-01

'Citizen Science' and 'Big data' are terms that are currently ubiquitous in the field of science communication. Whilst opinions differ as to what exactly constitutes a 'citizen', and how much information is needed in order for a data set to be considered truly 'big', what is apparent is that both of these fields have the potential to help revolutionise not just the way that science is communicated, but also the way that it is conducted. However, both the generation of sufficient data, and the efficiency of then analysing the data once it has been analysed need to be taken into account. Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral. The process of sentiment analysis can be automated, providing that an adequate training set has been used, and that the nuances that are associated with a particular topic have been accounted for. Given the large amounts of data that are generated by social media posts, and the often-opinionated nature of these posts, they present an ideal source of data to both train with and then scrutinize using sentiment analysis. In this work we will demonstrate how sentiment analysis can be used to examine a large number of Twitter posts, and how a training set can be established to ensure consistency and accuracy in the automation. Following an explanation of the process, we will demonstrate how automated sentiment analysis can be used to categorise opinions in relation to a large-scale science festival, and will discuss if sentiment analysis can be used to tell us if there is a bias in these communications. We will also investigate if sentiment analysis can be used to replace more traditional, and invasive evaluation strategies, and how this approach can then be adopted to investigate other topics, both within scientific communication and in the wider scientific context.

Social Media Sentiment Analysis and Topic Detection for Singapore English

Science.gov (United States)

2013-09-01

study of NLP techniques,” La Revista de Procesamiento de Lenguaje Natural , vol. 50, pp. 45–52, 2013. [5] F. Batista, and R. Ribeiro, “Sentiment...have been made possible via social-media applications. Sentiment analysis and topic detection are two growing areas in Natural Language Processing...social-media applications. Sentiment analysis and topic detection are two growing areas in Natural Language Processing, and there are increasing

Selling Sentiment: The Commodification of Emotion in Victorian Visual Culture

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Sonia Solicari

2007-04-01

Full Text Available This essay argues that the Victorian sentimental impulse was motivated by the sharing of emotion and the dynamics of communal and interactive feeling. Integral to the popularity of sentiment was its recognition factor by means of established tropes and conventions. Arguably, the same familiarity that made narrative art accessible also made advertising successful and many of the same motifs ran from exhibition watercolours to book illustration to posters. Works of sentiment operated as emotional souvenirs so that material proof of feeling could be easily digested, displayed and revisited. The essay looks closer at the investment of emotion in ephemeral images, such as music-sheet covers, and the ways in which forms of feeling were standardised and reproduced in keeping with a new art-buying public and the possibilities of wider image dissemination. Focusing upon issues raised during the curation of a current exhibition at the Victoria and Albert Museum ( 'A Show of Emotion: Victorian Sentiment in Prints and Drawings', 7 Dec 2006 – 10 Sep 2007 this essay explores the ways in which the sentimental pervaded nineteenth-century visual culture and how, in the cut-throat commercial world of image production, sentiment became manifest and identifiable if only as a notional phenomenon.

Microblog sentiment analysis using social and topic context.

Science.gov (United States)

Zou, Xiaomei; Yang, Jing; Zhang, Jianpei

2018-01-01

Analyzing massive user-generated microblogs is very crucial in many fields, attracting many researchers to study. However, it is very challenging to process such noisy and short microblogs. Most prior works only use texts to identify sentiment polarity and assume that microblogs are independent and identically distributed, which ignore microblogs are networked data. Therefore, their performance is not usually satisfactory. Inspired by two sociological theories (sentimental consistency and emotional contagion), in this paper, we propose a new method combining social context and topic context to analyze microblog sentiment. In particular, different from previous work using direct user relations, we introduce structure similarity context into social contexts and propose a method to measure structure similarity. In addition, we also introduce topic context to model the semantic relations between microblogs. Social context and topic context are combined by the Laplacian matrix of the graph built by these contexts and Laplacian regularization are added into the microblog sentiment analysis model. Experimental results on two real Twitter datasets demonstrate that our proposed model can outperform baseline methods consistently and significantly.

Sentiment and art prices

NARCIS (Netherlands)

Penasse, J.N.G.; Renneboog, L.D.R.; Spaenjers, C.

We hypothesize the existence of a slow-moving fad component in art prices. Using unique panel survey data on art market participants’ confidence levels in the outlook for a set of artists, we find that sentiment indeed predicts short-term returns.

Analyzing online sentiment to predict telephone poll results.

Science.gov (United States)

Fu, King-wa; Chan, Chee-hon

2013-09-01

The telephone survey is a common social science research method for capturing public opinion, for example, an individual's values or attitudes, or the government's approval rating. However, reducing domestic landline usage, increasing nonresponse rate, and suffering from response bias of the interviewee's self-reported data pose methodological challenges to such an approach. Because of the labor cost of administration, a phone survey is often conducted on a biweekly or monthly basis, and therefore a daily reflection of public opinion is usually not available. Recently, online sentiment analysis of user-generated content has been deployed to predict public opinion and human behavior. However, its overall effectiveness remains uncertain. This study seeks to examine the temporal association between online sentiment reflected in social media content and phone survey poll results in Hong Kong. Specifically, it aims to find the extent to which online sentiment can predict phone survey results. Using autoregressive integrated moving average time-series analysis, this study suggested that online sentiment scores can lead phone survey results by about 8-15 days, and their correlation coefficients were about 0.16. The finding is significant to the study of social media in social science research, because it supports the conclusion that daily sentiment observed in social media content can serve as a leading predictor for phone survey results, keeping as much as 2 weeks ahead of the monthly announcement of opinion polls. We also discuss the practical and theoretical implications of this study.

THE EFFECT OF INVESTOR SENTIMENT ON ISE SECTOR INDICES

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SERPİL CANBAŞ

2013-06-01

Full Text Available Determining the factors that affect stock returns is one of the most investigated topics of the finance literature. A number of models have been developed to explain stock returns. Some of these models maintain that stock returns are generated rationally. These models are, Capital Asset Pricing Model, Index Models, Arbitrage Pricing Model and Macroeconomic Factor Models. Nevertheless, these models could not have explained stock returns, although they have used different parameters and methods. Some studies have maintained that investor psychology would have a role in the stock return generation process. There are three theories that investigate the effect of investor psychology on financial markets: Mental accounting theory, herd behavior theory and investor sentiment theory. The aim of this study is to investigate the effect of investor sentiment on stock returns. In this context, three investor sentiment proxies have been determined in the light of previous studies. These proxies are closed-end fund discount, average fund flow of mutual funds and the ratio of net stock purchases of foreign investors to ISE market capitalization. ISE sector indices are used to proxy stock returns. On the other hand, there is a possibility that investor sentiment would merely reflect economic innovations. Some economic factors are used as control variables in order to examine this possibility. Regression analyses are employed for investigating the effect of investor sentiment on stock returns. Findings suggest that investor sentiment affect stock returns systematically. This finding keeps its robustness when economic variables are added to the model.

An Empirical Study of the Effect of Investor Sentiment on Returns of Different Industries

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Chuangxia Huang

2014-01-01

Full Text Available Studies on investor sentiment are mostly focused on the stock market, but little attention has been paid to the effect of investor sentiment on the return of a specific industry. This paper constructs a proxy variable to examine the relationship between investor sentiment and the return of a specific industry, using the Principle Component Analysis, and finds that investor sentiment is positively correlated with the industry return of the current period and negatively correlated with that of one lag period; we classify investor sentiment as optimistic state and pessimistic state and find that optimistic investor sentiment has a positive effect on stock returns of most industries, while pessimistic investor sentiment has no effect on them; this paper further builds a two-state Markov regime switching model and finds that sentiment has different effect on different industries returns on different states of market.

Identifying Sentiment of Hookah-Related Posts on Twitter.

Science.gov (United States)

Allem, Jon-Patrick; Ramanujam, Jagannathan; Lerman, Kristina; Chu, Kar-Hai; Boley Cruz, Tess; Unger, Jennifer B

2017-10-18

The increasing popularity of hookah (or waterpipe) use in the United States and elsewhere has consequences for public health because it has similar health risks to that of combustible cigarettes. While hookah use rapidly increases in popularity, social media data (Twitter, Instagram) can be used to capture and describe the social and environmental contexts in which individuals use, perceive, discuss, and are marketed this tobacco product. These data may allow people to organically report on their sentiment toward tobacco products like hookah unprimed by a researcher, without instrument bias, and at low costs. This study describes the sentiment of hookah-related posts on Twitter and describes the importance of debiasing Twitter data when attempting to understand attitudes. Hookah-related posts on Twitter (N=986,320) were collected from March 24, 2015, to December 2, 2016. Machine learning models were used to describe sentiment on 20 different emotions and to debias the data so that Twitter posts reflected sentiment of legitimate human users and not of social bots or marketing-oriented accounts that would possibly provide overly positive or overly negative sentiment of hookah. From the analytical sample, 352,116 tweets (59.50%) were classified as positive while 177,537 (30.00%) were classified as negative, and 62,139 (10.50%) neutral. Among all positive tweets, 218,312 (62.00%) were classified as highly positive emotions (eg, active, alert, excited, elated, happy, and pleasant), while 133,804 (38.00%) positive tweets were classified as passive positive emotions (eg, contented, serene, calm, relaxed, and subdued). Among all negative tweets, 95,870 (54.00%) were classified as subdued negative emotions (eg, sad, unhappy, depressed, and bored) while the remaining 81,667 (46.00%) negative tweets were classified as highly negative emotions (eg, tense, nervous, stressed, upset, and unpleasant). Sentiment changed drastically when comparing a corpus of tweets with social bots

Semantic network analysis of vaccine sentiment in online social media.

Science.gov (United States)

Kang, Gloria J; Ewing-Nelson, Sinclair R; Mackey, Lauren; Schlitt, James T; Marathe, Achla; Abbas, Kaja M; Swarup, Samarth

2017-06-22

To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage

Anti-Halal and Anti-Animal Slaughtering Campaigns and Their Impact in Post-War Sri Lanka

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Mohammad Agus Yusoff

2017-03-01

Full Text Available This paper aims to examine the overall impact of anti-halal and anti-slaughtering campaigns in the context of post-war Sri Lanka. The reemergence of majoritarian ethno-religious anti-minority nationalist forces and their intensified anti-minority hatred and violence have made it challenging for ethno-religious minorities in Sri Lanka to engage in religious norms and duties. This is especially true for the Muslim community. Numerous Islamic fundamentals have been criticized and opposed. Muslims have had to endure threats and acts of violence. These campaigns and violent oppositions, imposed by the Buddhist-nationalist forces, have caused concern for Muslims performing their obligatory religious duties and norms. In Sri Lanka, the Muslim community has been allowed to produce halal food and slaughter animals for human consumption and religious rituals for a long period without disturbance. Unfortunately, retaliation and hatred in the post-civil war era in the country have threatened these rights. Thus, it has become imperative to investigate the motivating factors of the anti-halal and anti-animal slaughtering campaigns and violence, as well as their related impact, which is lacking in the existing literature on ethno-religious politics in the context of Sri Lanka. This study found that the anti-halal and anti-animal slaughtering campaigns and oppositions that have been intensified by the Buddhist nationalist forces were part of anti-Muslim sentiments intended to sabotage the economic pride of Muslims and undermine their religious renaissance. The study also found that these campaigns have been facilitated by the state and that continuous facilitation of the anti-Muslim sentiments and campaigns, including the anti-halal and anti-animal slaughter campaigns, would challenge the country’s economic prosperity and the rebuilding of ethno-religious harmony.

Sentiment analysis of political communication: combining a dictionary approach with crowdcoding.

Science.gov (United States)

Haselmayer, Martin; Jenny, Marcelo

2017-01-01

Sentiment is important in studies of news values, public opinion, negative campaigning or political polarization and an explosive expansion of digital textual data and fast progress in automated text analysis provide vast opportunities for innovative social science research. Unfortunately, tools currently available for automated sentiment analysis are mostly restricted to English texts and require considerable contextual adaption to produce valid results. We present a procedure for collecting fine-grained sentiment scores through crowdcoding to build a negative sentiment dictionary in a language and for a domain of choice. The dictionary enables the analysis of large text corpora that resource-intensive hand-coding struggles to cope with. We calculate the tonality of sentences from dictionary words and we validate these estimates with results from manual coding. The results show that the crowdbased dictionary provides efficient and valid measurement of sentiment. Empirical examples illustrate its use by analyzing the tonality of party statements and media reports.

Anomalies and Investor Sentiment: Empirical Evidences in the Brazilian Market

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Gustavo Correia Xavier

2017-10-01

Full Text Available This study examined the relationship between investor sentiment and value anomalies in Brazil. In addition, it analyzed if pricing deviations caused by investors with optimistic views are different from those caused by pessimistic investors. The sample included all non-financial firms listed on the B3 (Brasil, Bolsa, Balcão stock exchange from July 1999 to June 2014. We used the Principal Component Analysis multivariate technique to capture the component common to four different proxies for investor sentiment. The study empirically tested the index series and its variation on the return series of Long-Short portfolios of 12 anomaly-based strategies. The study found that the measure of the sentiment index had a partial explanatory power for the anomalies only when included in the CAPM. Yet, when using the index sentiment changes as an explanatory variable, the study found a relationship with future returns, robust to all risk factors. Thus, it is possible to relate investor sentiment index to anomaly-based portfolio returns. When analyzing average returns after optimistic and pessimistic periods, the values we found in our empirical test were not statistically significant enough to infer the possible existence of short-sale constraints.

Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs

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Andrew J Reagan

2017-10-01

Full Text Available Abstract The emergence and global adoption of social media has rendered possible the real-time estimation of population-scale sentiment, an extraordinary capacity which has profound implications for our understanding of human behavior. Given the growing assortment of sentiment-measuring instruments, it is imperative to understand which aspects of sentiment dictionaries contribute to both their classification accuracy and their ability to provide richer understanding of texts. Here, we perform detailed, quantitative tests and qualitative assessments of 6 dictionary-based methods applied to 4 different corpora, and briefly examine a further 20 methods. We show that while inappropriate for sentences, dictionary-based methods are generally robust in their classification accuracy for longer texts. Most importantly they can aid understanding of texts with reliable and meaningful word shift graphs if (1 the dictionary covers a sufficiently large portion of a given text’s lexicon when weighted by word usage frequency; and (2 words are scored on a continuous scale.

A new ANEW: Evaluation of a word list for sentiment analysis in microblogs

DEFF Research Database (Denmark)

Nielsen, Finn Årup

2011-01-01

Sentiment analysis of microblogs such as Twitter has recently gained a fair amount of attention. One of the simplest sentiment analysis approaches compares the words of a posting against a labeled word list, where each word has been scored for valence, — a “sentiment lexicon” or “affective word...... lists”. There exist several affective word lists, e.g., ANEW (Affective Norms for English Words) developed before the advent of microblogging and sentiment analysis. I wanted to examine how well ANEW and other word lists performs for the detection of sentiment strength in microblog posts in comparison...... with a new word list specifically constructed for microblogs. I used manually labeled postings from Twitter scored for sentiment. Using a simple word matching I show that the new word list may perform better than ANEW, though not as good as the more elaborate approach found in SentiStrength....

Inequality and anti-globalization backlash by political parties

NARCIS (Netherlands)

Burgoon, B.

2011-01-01

Does inequality fuel anti-globalization backlash? This paper answers this question by analyzing how income inequality affects the embrace or eschew of globalization by political parties. It focuses on party opposition to and support for trade openness, European-Union integration, and general

Toward understanding online sentiment expression: an interdisciplinary approach with subgroup comparison and visualization

NARCIS (Netherlands)

Gao, B.; Berendt, B.; Vanschoren, J.

2016-01-01

Understanding users’ sentiment expression in social media is important in many domains, such as marketing and online applications. Is one demographic group inherently different from another? Does a group express the same sentiment both in private and public? How can we compare the sentiments of

SAFE: A Sentiment Analysis Framework for E-Learning

Directory of Open Access Journals (Sweden)

Francesco Colace

2014-12-01

Full Text Available The spread of social networks allows sharing opinions on different aspects of life and daily millions of messages appear on the web. This textual information can be a rich source of data for opinion mining and sentiment analysis: the computational study of opinions, sentiments and emotions expressed in a text. Its main aim is the identification of the agreement or disagreement statements that deal with positive or negative feelings in comments or reviews. In this paper, we investigate the adoption, in the field of the e-learning, of a probabilistic approach based on the Latent Dirichlet Allocation (LDA as Sentiment grabber. By this approach, for a set of documents belonging to a same knowledge domain, a graph, the Mixed Graph of Terms, can be automatically extracted. The paper shows how this graph contains a set of weighted word pairs, which are discriminative for sentiment classification. In this way, the system can detect the feeling of students on some topics and teacher can better tune his/her teaching approach. In fact, the proposed method has been tested on datasets coming from e-learning platforms. A preliminary experimental campaign shows how the proposed approach is effective and satisfactory.

Naturalist Sentimentalism

DEFF Research Database (Denmark)

Wohlmann, Anita

2018-01-01

This article examines four short stories by the American writer Rebecca Harding Davis (1831-1910), who became a nationally acclaimed writer with the stylistically innovative novella Life in the Iron Mills (1861). Using the double perspective of age studies and ‘naturalist sentimentalism’, the essay...... analyses Davis’s representation of the paradoxes of old age. Davis blends sentimental ideals of sympathy, sacrifice, and hope with naturalist themes of entrapment, the inevitability of decline, and biological determinism. Four short stories by Davis will serve as cases in point: ‘At Noon’ (1887), ‘At...

Revisiting the investor sentiment-stock returns relationship: A multi-scale perspective using wavelets

Science.gov (United States)

Lao, Jiashun; Nie, He; Jiang, Yonghong

2018-06-01

This paper employs SBW proposed by Baker and Wurgler (2006) to investigate the nonlinear asymmetric Granger causality between investor sentiment and stock returns for US economy while considering different time-scales. The wavelet method is utilized to decompose time series of investor sentiment and stock returns at different time-scales to focus on the local analysis of different time horizons of investors. The linear and nonlinear asymmetric Granger methods are employed to examine the Granger causal relationship on similar time-scales. We find evidence of strong bilateral linear and nonlinear asymmetric Granger causality between longer-term investor sentiment and stock returns. Furthermore, we observe the positive nonlinear causal relationship from stock returns to investor sentiment and the negative nonlinear causal relationship from investor sentiment to stock returns.

Wavelets and Sentiment in the Heterogeneous Agents Model

Czech Academy of Sciences Publication Activity Database

Vácha, Lukáš; Vošvrda, Miloslav

2008-01-01

Roč. 15, č. 25 (2008), s. 41-56 ISSN 1212-074X R&D Projects: GA ČR GP402/08/P207; GA ČR GA402/07/1113; GA ČR(CZ) GA402/06/0990 Institutional research plan: CEZ:AV0Z10750506 Keywords : heterogeneous agents model * market sentiment * Hurst exponent * wavelets Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2008/E/vacha-wavelets and sentiment in the heterogeneous agents model.pdf

Sentiment Analysis of Web Sites Related to Vaginal Mesh Use in Pelvic Reconstructive Surgery.

Science.gov (United States)

Hobson, Deslyn T G; Meriwether, Kate V; Francis, Sean L; Kinman, Casey L; Stewart, J Ryan

2018-05-02

The purpose of this study was to utilize sentiment analysis to describe online opinions toward vaginal mesh. We hypothesized that sentiment in legal Web sites would be more negative than that in medical and reference Web sites. We generated a list of relevant key words related to vaginal mesh and searched Web sites using the Google search engine. Each unique uniform resource locator (URL) was sorted into 1 of 6 categories: "medical", "legal", "news/media", "patient generated", "reference", or "unrelated". Sentiment of relevant Web sites, the primary outcome, was scored on a scale of -1 to +1, and mean sentiment was compared across all categories using 1-way analysis of variance. Tukey test evaluated differences between category pairs. Google searches of 464 unique key words resulted in 11,405 URLs. Sentiment analysis was performed on 8029 relevant URLs (3472 legal, 1625 "medical", 1774 "reference", 666 "news media", 492 "patient generated"). The mean sentiment for all relevant Web sites was +0.01 ± 0.16; analysis of variance revealed significant differences between categories (P Web sites categorized as "legal" and "news/media" had a slightly negative mean sentiment, whereas those categorized as "medical," "reference," and "patient generated" had slightly positive mean sentiments. Tukey test showed differences between all category pairs except the "medical" versus "reference" in comparison with the largest mean difference (-0.13) seen in the "legal" versus "reference" comparison. Web sites related to vaginal mesh have an overall mean neutral sentiment, and Web sites categorized as "medical," "reference," and "patient generated" have significantly higher sentiment scores than related Web sites in "legal" and "news/media" categories.

UT-DB: an experimental study on sentiment analysis in twitter

NARCIS (Netherlands)

Zhu, Zhemin; Hiemstra, Djoerd; Apers, Peter M.G.; Wombacher, Andreas

This paper describes our system for participating SemEval2013 Task2-B (Kozareva et al., 2013): Sentiment Analysis in Twitter. Given a message, our system classifies whether the message is positive, negative or neutral sentiment. It uses a co-occurrence rate model. The training data are constrained

A Framework for Sentiment Analysis Implementation of Indonesian Language Tweet on Twitter

Science.gov (United States)

Asniar; Aditya, B. R.

2017-01-01

Sentiment analysis is the process of understanding, extracting, and processing the textual data automatically to obtain information. Sentiment analysis can be used to see opinion on an issue and identify a response to something. Millions of digital data are still not used to be able to provide any information that has usefulness, especially for government. Sentiment analysis in government is used to monitor the work programs of the government such as the Government of Bandung City through social media data. The analysis can be used quickly as a tool to see the public response to the work programs, so the next strategic steps can be taken. This paper adopts Support Vector Machine as a supervised algorithm for sentiment analysis. It presents a framework for sentiment analysis implementation of Indonesian language tweet on twitter for Work Programs of Government of Bandung City. The results of this paper can be a reference for decision making in local government.

Measuring e-Commerce service quality from online customer review using sentiment analysis

Science.gov (United States)

Kencana Sari, Puspita; Alamsyah, Andry; Wibowo, Sulistyo

2018-03-01

The biggest e-Commerce challenge to understand their market is to chart their level of service quality according to customer perception. The opportunities to collect user perception through online user review is considered faster methodology than conducting direct sampling methodology. To understand the service quality level, sentiment analysis methodology is used to classify the reviews into positive and negative sentiment for five dimensions of electronic service quality (e-Servqual). As case study in this research, we use Tokopedia, one of the biggest e-Commerce service in Indonesia. We obtain the online review comments about Tokopedia service quality during several month observations. The Naïve Bayes classification methodology is applied for the reason of its high-level accuracy and support large data processing. The result revealed that personalization and reliability dimension required more attention because have high negative sentiment. Meanwhile, trust and web design dimension have high positive sentiments that means it has very good services. The responsiveness dimension have balance sentiment positive and negative.

Sentiments and Perceptions of Business Respondents on Social Media: an Exploratory Analysis

OpenAIRE

Torres van Grinsven Vanessa; Snijkers Ger

2015-01-01

The perceptions and sentiments of business respondents are considered important for statistical bureaus. As perceptions and sentiments are related to the behavior of the people expressing them, gaining insights into the perceptions and sentiments of business respondents is of interest to understand business survey response. In this article we present an exploratory analysis of expressions in the social media regarding Statistics Netherlands. In recent years, social media have become an import...

Accentuate the Positive: Positive Sentiments and Status in Task Groups

Science.gov (United States)

Bianchi, Alison J.; Lancianese, Donna A.

2007-01-01

We explore the capacity of positive sentiments, those enduring affective states one achieves when one likes another, to impact status structures. Do positive sentiments combine with existing aspects of interaction to create status hierarchies and potentially change the social order, or do they moderate the effects of extant structure by dampening…

Logical Entity Level Sentiment Analysis

DEFF Research Database (Denmark)

Petersen, Niklas Christoffer; Villadsen, Jørgen

2017-01-01

We present a formal logical approach using a combinatory categorial grammar for entity level sentiment analysis that utilizes machine learning techniques for efficient syntactical tagging and performs a deep structural analysis of the syntactical properties of texts in order to yield precise resu...

The Impact of Conventional and Unconventional Monetary Policy on Investor Sentiment

DEFF Research Database (Denmark)

Lutz, Chandler

2015-01-01

This paper examines the relationship between monetary policy and investor sentiment across conventional and unconventional monetary policy regimes. During conventional times, we find that a surprise decrease in the fed funds rate leads to a large increase in investor sentiment. Similarly, when...... the fed funds rate is at its zero lower bound, research results indicate that expansionary unconventional monetary policy shocks also have a large and positive impact on investor mood. Together, our findings highlight the importance of both conventional and unconventional monetary policy...... in the determination of investor sentiment....

Measuring political sentiment on Twitter: factor-optimal design for multinomial inverse regression

OpenAIRE

Taddy, Matt

2012-01-01

This article presents a short case study in text analysis: the scoring of Twitter posts for positive, negative, or neutral sentiment directed towards particular US politicians. The study requires selection of a sub-sample of representative posts for sentiment scoring, a common and costly aspect of sentiment mining. As a general contribution, our application is preceded by a proposed algorithm for maximizing sampling efficiency. In particular, we outline and illustrate greedy selection of docu...

Sentiment Polarity Analysis based multi-dictionary

Science.gov (United States)

Jiao, Jian; Zhou, Yanquan

This paper presents a novel algorithm for Chinese online reviews, which identifies sentiment polarity. To determine the sentence is negative or positive, we extracted opinion words and identified their opinion targets by CRFs and establish the absolute emotional dictionary (AbED), the relative emotional dictionary (ReED), the field of emotional dictionary (FiED) and the field of targets and opinion words dictionary (TfED). With those emotional dictionary, negative dictionary and modified dictionary, we achieved an effective algorithm to discriminate sentiment polarity by multi-string pattern matching algorithm. For evaluation, we used car online reviews, hotel online reviews and computer online reviews which annotated positive or negative. Experimental results show that our proposed method has made a higher precision and recall rate.

Aspect-based sentiment analysis to review products using Naïve Bayes

Science.gov (United States)

Mubarok, Mohamad Syahrul; Adiwijaya, Aldhi, Muhammad Dwi

2017-08-01

Product reviews can provide great benefits for consumers and producers. Number of reviews could be ranging from hundreds to thousands and containing various opinions. These make the process of analyzing and extracting information on existing reviews become increasingly difficult. In this research, sentiment analysis was used to analyze and extract sentiment polarity on product reviews based on a specific aspect of the product. This research was conducted in three phases, such as data preprocessing which involves part-of-speech (POS) tagging, feature selection using Chi Square, and classification of sentiment polarity of aspects using Naïve Bayes. Based on evaluation results, it is known that the system is able to perform aspect-based sentiment analysis with its highest F1-Measure of 78.12%.

Choosing your weapons : on sentiment analysis tools for software engineering research

NARCIS (Netherlands)

Jongeling, R.M.; Datta, S.; Serebrenik, A.; Koschke, R.; Krinke, J.; Robillard, M.

2015-01-01

Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these

Sentiment analysis and the impact of employee satisfaction on firm earnings

NARCIS (Netherlands)

A.J. Moniz (Andy); F.M.G. de Jong (Franciska)

2014-01-01

textabstractPrior text mining studies of corporate reputational sentiment based on newswires, blogs and Twitter feeds have mostly captured reputation from the perspective of two groups of stakeholders - the media and consumers. In this study we examine the sentiment of a potentially overlooked

Automatic Construction and Global Optimization of a Multisentiment Lexicon

Directory of Open Access Journals (Sweden)

Xiaoping Yang

2016-01-01

Full Text Available Manual annotation of sentiment lexicons costs too much labor and time, and it is also difficult to get accurate quantification of emotional intensity. Besides, the excessive emphasis on one specific field has greatly limited the applicability of domain sentiment lexicons (Wang et al., 2010. This paper implements statistical training for large-scale Chinese corpus through neural network language model and proposes an automatic method of constructing a multidimensional sentiment lexicon based on constraints of coordinate offset. In order to distinguish the sentiment polarities of those words which may express either positive or negative meanings in different contexts, we further present a sentiment disambiguation algorithm to increase the flexibility of our lexicon. Lastly, we present a global optimization framework that provides a unified way to combine several human-annotated resources for learning our 10-dimensional sentiment lexicon SentiRuc. Experiments show the superior performance of SentiRuc lexicon in category labeling test, intensity labeling test, and sentiment classification tasks. It is worth mentioning that, in intensity label test, SentiRuc outperforms the second place by 21 percent.

Aspect level sentiment analysis using machine learning

Science.gov (United States)

Shubham, D.; Mithil, P.; Shobharani, Meesala; Sumathy, S.

2017-11-01

In modern world the development of web and smartphones increases the usage of online shopping. The overall feedback about product is generated with the help of sentiment analysis using text processing.Opinion mining or sentiment analysis is used to collect and categorized the reviews of product. The proposed system uses aspect leveldetection in which features are extracted from the datasets. The system performs pre-processing operation such as tokenization, part of speech and limitization on the data tofinds meaningful information which is used to detect the polarity level and assigns rating to product. The proposed model focuses on aspects to produces accurate result by avoiding the spam reviews.

Information, Sentiment, and Price in a Fast Order-Driven Market

Czech Academy of Sciences Publication Activity Database

Derviz, Alexis

2011-01-01

Roč. 8, č. 3 (2011), s. 43-75 ISSN 0972-916X Institutional research plan: CEZ:AV0Z10750506 Keywords : limit order * market order * high frequency trading * price dicovery * sentiment Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2011/E/derviz-information, sentiment, and price in a fast order-driven market.pdf

Sentiment analysis and the impact of employee satisfaction on firm earnings

NARCIS (Netherlands)

Moniz, Andy; de Jong, Franciska M.G.

Prior text mining studies of corporate reputational sentiment based on newswires, blogs and Twitter feeds have mostly captured reputation from the perspective of two groups of stakeholders – the media and consumers. In this study we examine the sentiment of a potentially overlooked stakeholder

Does Online Investor Sentiment Affect the Asset Price Movement? Evidence from the Chinese Stock Market

Directory of Open Access Journals (Sweden)

Chi Xie

2017-01-01

Full Text Available With the quick development of the Internet, online platforms that provide financial news and opinions have attracted more and more attention from investors. The question whether investor sentiment expressed on the Internet platforms has an impact on asset return has not been fully addressed. To this end, this paper uses the Baidu Searching Index as the agent variable to detect the effect of online investor sentiment on the asset price movement in the Chinese stock market. The empirical study shows that although there is a cointegration relationship between online investor sentiment and asset return, the sentiment has a poor ability to predict the price, return, and volatility of asset price. Meanwhile, the structural break points of online investor sentiment do not lead to changes in the asset price movement. Based on the empirical mode decomposition of online investor sentiment, we find that high frequency components of online investor sentiment can be used to predict the asset price movement. Thus, the obtained results could be useful for risk supervision and asset portfolio management.

DEEP LEARNING MODEL FOR BILINGUAL SENTIMENT CLASSIFICATION OF SHORT TEXTS

Directory of Open Access Journals (Sweden)

Y. B. Abdullin

2017-01-01

Full Text Available Sentiment analysis of short texts such as Twitter messages and comments in news portals is challenging due to the lack of contextual information. We propose a deep neural network model that uses bilingual word embeddings to effectively solve sentiment classification problem for a given pair of languages. We apply our approach to two corpora of two different language pairs: English-Russian and Russian-Kazakh. We show how to train a classifier in one language and predict in another. Our approach achieves 73% accuracy for English and 74% accuracy for Russian. For Kazakh sentiment analysis, we propose a baseline method, that achieves 60% accuracy; and a method to learn bilingual embeddings from a large unlabeled corpus using a bilingual word pairs.

Public Perceptions of Aquaculture: Evaluating Spatiotemporal Patterns of Sentiment around the World.

Directory of Open Access Journals (Sweden)

Halley E Froehlich

Full Text Available Aquaculture is developing rapidly at a global scale and sustainable practices are an essential part of meeting the protein requirements of the ballooning human population. Locating aquaculture offshore is one strategy that may help address some issues related to nearshore development. However, offshore production is nascent and distinctions between the types of aquatic farming may not be fully understood by the public-important for collaboration, research, and development. Here we evaluate and report, to our knowledge, the first multinational quantification of the relative sentiments and opinions of the public around distinct forms of aquaculture. Using thousands of newspaper headlines (Ntotal = 1,596 from developed (no. countries = 26 and developing (42 nations, ranging over periods of 1984 to 2015, we found an expanding positive trend of general 'aquaculture' coverage, while 'marine' and 'offshore' appeared more negative. Overall, developing regions published proportionally more positive than negative headlines than developed countries. As case studies, government collected public comments (Ntotal = 1,585 from the United States of America (USA and New Zealand mirrored the media sentiments; offshore perception being particularly negative in the USA. We also found public sentiment may be influenced by local environmental disasters not directly related to aquaculture (e.g., oil spills. Both countries voiced concern over environmental impacts, but the concerns tended to be more generalized, rather than targeted issues. Two factors that could be inhibiting informed discussion and decisions about offshore aquaculture are lack of applicable knowledge and actual local development issues. Better communication and investigation of the real versus perceived impacts of aquaculture could aid in clarifying the debate about aquaculture, and help support future sustainable growth.

Sentiment analysis system for movie review in Bahasa Indonesia using naive bayes classifier method

Science.gov (United States)

Nurdiansyah, Yanuar; Bukhori, Saiful; Hidayat, Rahmad

2018-04-01

There are many ways of implementing the use of sentiments often found in documents; one of which is the sentiments found on the product or service reviews. It is so important to be able to process and extract textual data from the documents. Therefore, we propose a system that is able to classify sentiments from review documents into two classes: positive sentiment and negative sentiment. We use Naive Bayes Classifier method in this document classification system that we build. We choose Movienthusiast, a movie reviews in Bahasa Indonesia website as the source of our review documents. From there, we were able to collect 1201 movie reviews: 783 positive reviews and 418 negative reviews that we use as the dataset for this machine learning classifier. The classifying accuracy yields an average of 88.37% from five times of accuracy measuring attempts using aforementioned dataset.

Twitter Sentiment Analysis Applied to Finance: A Case Study in the Retail Industry

OpenAIRE

Th\\'arsis Tuani Pinto Souza; Olga Kolchyna; Philip C. Treleaven; Tomaso Aste

2015-01-01

This paper presents a financial analysis over Twitter sentiment analytics extracted from listed retail brands. We investigate whether there is statistically-significant information between the Twitter sentiment and volume, and stock returns and volatility. Traditional newswires are also considered as a proxy for the market sentiment for comparative purpose. The results suggest that social media is indeed a valuable source in the analysis of the financial dynamics in the retail sector even whe...

The Effects of Twitter Sentiment on Stock Price Returns.

Science.gov (United States)

Ranco, Gabriele; Aleksovski, Darko; Caldarelli, Guido; Grčar, Miha; Mozetič, Igor

2015-01-01

Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-known micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2%), but the dependence is statistically significant for several days after the events.

Harmonization of anti-doping rules in a global context (World Anti-Doping Agency-laboratory accreditation perspective).

Science.gov (United States)

Ivanova, Victoria; Miller, John H M; Rabin, Olivier; Squirrell, Alan; Westwood, Steven

2012-07-01

This article provides a review of the leading role of the World Anti-Doping Agency (WADA) in the context of the global fight against doping in sport and the harmonization of anti-doping rules worldwide through the implementation of the World Anti-Doping Program. Particular emphasis is given to the WADA-laboratory accreditation program, which is coordinated by the Science Department of WADA in conjunction with the Laboratory Expert Group, and the cooperation with the international accreditation community through International Laboratory Accreditation Cooperation and other organizations, all of which contribute to constant improvement of laboratory performance in the global fight against doping in sport. A perspective is provided of the means to refine the existing anti-doping rules and programs to ensure continuous improvement in order to face growing sophisticated challenges. A viewpoint on WADA's desire to embrace cooperation with other international organizations whose knowledge can contribute to the fight against doping in sport is acknowledged.

Assessing vaccination sentiments with online social media: implications for infectious disease dynamics and control.

Science.gov (United States)

Salathé, Marcel; Khandelwal, Shashank

2011-10-01

There is great interest in the dynamics of health behaviors in social networks and how they affect collective public health outcomes, but measuring population health behaviors over time and space requires substantial resources. Here, we use publicly available data from 101,853 users of online social media collected over a time period of almost six months to measure the spatio-temporal sentiment towards a new vaccine. We validated our approach by identifying a strong correlation between sentiments expressed online and CDC-estimated vaccination rates by region. Analysis of the network of opinionated users showed that information flows more often between users who share the same sentiments - and less often between users who do not share the same sentiments - than expected by chance alone. We also found that most communities are dominated by either positive or negative sentiments towards the novel vaccine. Simulations of infectious disease transmission show that if clusters of negative vaccine sentiments lead to clusters of unprotected individuals, the likelihood of disease outbreaks is greatly increased. Online social media provide unprecedented access to data allowing for inexpensive and efficient tools to identify target areas for intervention efforts and to evaluate their effectiveness.

On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis

Directory of Open Access Journals (Sweden)

Asriyanti Indah Pratiwi

2018-01-01

Full Text Available Sentiment analysis in a movie review is the needs of today lifestyle. Unfortunately, enormous features make the sentiment of analysis slow and less sensitive. Finding the optimum feature selection and classification is still a challenge. In order to handle an enormous number of features and provide better sentiment classification, an information-based feature selection and classification are proposed. The proposed method reduces more than 90% unnecessary features while the proposed classification scheme achieves 96% accuracy of sentiment classification. From the experimental results, it can be concluded that the combination of proposed feature selection and classification achieves the best performance so far.

Economic sentiment indicator and its information capability in the Czech Republic

Directory of Open Access Journals (Sweden)

Radka Martináková

2013-01-01

Full Text Available The paper focuses on the indicators of economic agents’ perceptions in the Czech Republic. We assume that these information are provided by economic sentiment indicator surveys based on the Joint Harmonised EU Programme. The aim of this paper is to offer the alternate methodology of qualitative data transformation (balance statistic data in relation with the macroeconomic quantitative indicators. In the empirical analysis we distinguished between the indicators of confidence in industry, construction, retail and consumer confidence indicator. We found link between the aggregate economic sentiment indicator and economic activity. Especially, aggregate economic sentiment indicator copies the development of the GDP. However, partial indicators does not follow changes in the specific sectors of the economy. We also found that economic agents underestimate the intensity of the economic recession after the year 2007.Finally, we cannot recommend the economic sentiment indicator as the leading indicator of the future economic activity in the Czech Republic. Our methodological contribution is in quantifying of the consumer survey results by standardization.

Determination of quality television programmes based on sentiment analysis on Twitter

Science.gov (United States)

Amalia, A.; Oktinas, W.; Aulia, I.; Rahmat, R. F.

2018-03-01

Public sentiment from social media like Twitter can be used as one of the indicators to determine the quality of TV Programmes. In this study, we implemented information extraction on Twitter by using sentiment analysis method to assess the quality of TV Programmes. The first stage of this study is pre-processing which consists of cleansing, case folding, tokenizing, stop-word removal, stemming, and redundancy filtering. The next stage is weighting process for every single word by using TF-IDF method. The last step of this study is the sentiment classification process which is divided into three sentiment category which is positive, negative and neutral. We classify the TV programmes into several categories such as news, children, or films/soap operas. We implemented an improved k-nearest neighbor method in classification 4000 twitter status, for four biggest TV stations in Indonesia, with ratio 70% data for training and 30% of data for the testing process. The result obtained from this research generated the highest accuracy with k=10 as big as 90%.

Optimizing Short Message Text Sentiment Analysis for Mobile Device Forensics

OpenAIRE

Aboluwarin , Oluwapelumi; Andriotis , Panagiotis; Takasu , Atsuhiro; Tryfonas , Theo

2016-01-01

Part 2: MOBILE DEVICE FORENSICS; International audience; Mobile devices are now the dominant medium for communications. Humans express various emotions when communicating with others and these communications can be analyzed to deduce their emotional inclinations. Natural language processing techniques have been used to analyze sentiment in text. However, most research involving sentiment analysis in the short message domain (SMS and Twitter) do not account for the presence of non-dictionary w...

Semantic Sentiment Analysis in Arabic Social Media

Directory of Open Access Journals (Sweden)

Samir Tartir

2017-04-01

Full Text Available Social media is a huge source of information. And is increasingly being used by governments, companies, and marketers to understand how the crowd thinks. Sentiment analysis aims to determine the attitudes of a group of people that are using one or more social media platforms with respect to a certain topic. In this paper, we propose a semantic approach to discover user attitudes and business insights from social media in Arabic, both standard and dialects. We also introduce the first version of our Arabic Sentiment Ontology (ASO that contains different words that express feelings and how strongly these words express these feelings. We then show the usability of our approach in classifying different Twitter feeds on different topics.

Investor sentiment, mutual fund flows and its impact on returns and volatility

NARCIS (Netherlands)

Lehnert, T.; Müller, A.; Frijns, B.P.M.; Beaumont, R.J.; Daele, M. van

2008-01-01

- Purpose – The purpose of this paper is to investigate the impact of individual investor sentiment on the return process and conditional volatility of three main US market indices (Dow Jones Industrial Average, S&P500 and Nasdaq100). Individual investor sentiment is measured by aggregate money

Assessing Anti-American Sentiment Through Social Media Analysis

Science.gov (United States)

2016-12-01

165 Yuri Kageyama, “Twitter Takes Off in Japan – Social Network Changes Nation’s Internet Culture,” Journal - Gazette, July 4, 2010, http...military shows of force in and around Japan . 14. SUBJECT TERMS anti-Americanism, Twitter, social media analysis; drone strike; Pakistan, UAV...hypothesizes that social media analysis, specifically analysis of messages sent through the Twitter network , can be used to gauge the overall

The Asymmetric Effects of Investor Sentiment

DEFF Research Database (Denmark)

Lutz, Chandler

investors only act as corrective force during certain time periods. We also show that our index predicts implied volatility, media pessimism, and mutual fund flows. Overall, our findings are consistent with both the theories and anecdotal accounts of investor sentiment in the stock market....

A mathematical model of sentimental dynamics accounting for marital dissolution.

Science.gov (United States)

Rey, José-Manuel

2010-03-31

Marital dissolution is ubiquitous in western societies. It poses major scientific and sociological problems both in theoretical and therapeutic terms. Scholars and therapists agree on the existence of a sort of second law of thermodynamics for sentimental relationships. Effort is required to sustain them. Love is not enough. Building on a simple version of the second law we use optimal control theory as a novel approach to model sentimental dynamics. Our analysis is consistent with sociological data. We show that, when both partners have similar emotional attributes, there is an optimal effort policy yielding a durable happy union. This policy is prey to structural destabilization resulting from a combination of two factors: there is an effort gap because the optimal policy always entails discomfort and there is a tendency to lower effort to non-sustaining levels due to the instability of the dynamics. These mathematical facts implied by the model unveil an underlying mechanism that may explain couple disruption in real scenarios. Within this framework the apparent paradox that a union consistently planned to last forever will probably break up is explained as a mechanistic consequence of the second law.

A mathematical model of sentimental dynamics accounting for marital dissolution.

Directory of Open Access Journals (Sweden)

José-Manuel Rey

Full Text Available BACKGROUND: Marital dissolution is ubiquitous in western societies. It poses major scientific and sociological problems both in theoretical and therapeutic terms. Scholars and therapists agree on the existence of a sort of second law of thermodynamics for sentimental relationships. Effort is required to sustain them. Love is not enough. METHODOLOGY/PRINCIPAL FINDINGS: Building on a simple version of the second law we use optimal control theory as a novel approach to model sentimental dynamics. Our analysis is consistent with sociological data. We show that, when both partners have similar emotional attributes, there is an optimal effort policy yielding a durable happy union. This policy is prey to structural destabilization resulting from a combination of two factors: there is an effort gap because the optimal policy always entails discomfort and there is a tendency to lower effort to non-sustaining levels due to the instability of the dynamics. CONCLUSIONS/SIGNIFICANCE: These mathematical facts implied by the model unveil an underlying mechanism that may explain couple disruption in real scenarios. Within this framework the apparent paradox that a union consistently planned to last forever will probably break up is explained as a mechanistic consequence of the second law.

Sarcastic sentiment detection in tweets streamed in real time: a big data approach

Directory of Open Access Journals (Sweden)

S.K. Bharti

2016-08-01

Full Text Available Sarcasm is a type of sentiment where people express their negative feelings using positive or intensified positive words in the text. While speaking, people often use heavy tonal stress and certain gestural clues like rolling of the eyes, hand movement, etc. to reveal sarcastic. In the textual data, these tonal and gestural clues are missing, making sarcasm detection very difficult for an average human. Due to these challenges, researchers show interest in sarcasm detection of social media text, especially in tweets. Rapid growth of tweets in volume and its analysis pose major challenges. In this paper, we proposed a Hadoop based framework that captures real time tweets and processes it with a set of algorithms which identifies sarcastic sentiment effectively. We observe that the elapse time for analyzing and processing under Hadoop based framework significantly outperforms the conventional methods and is more suited for real time streaming tweets.

Ranking product aspects through sentiment analysis of online reviews

Science.gov (United States)

Wang, Wei; Wang, Hongwei; Song, Yuan

2017-03-01

The electronic word-of-mouth (e-WOM) is one of the most important among all the factors affecting consumers' behaviours. Opinions towards a product through online reviews will influence purchase decisions of other online consumers by changing their perceptions on the product quality. Furthermore, each product aspect may impact consumers' intentions differently. Thus, sentiment analysis and econometric models are incorporated to examine the relationship between purchase intentions and aspect-opinion pairs, which enable the weight estimation for each product aspect. We first identify product aspects and reduce dimensions to extract aspect-opinion pairs. Next the information gain is calculated for each aspect through entropy theory. Based on sentiment polarity and sentiment strength, we formulate an econometric model by integrating the information gain to measure the aspect's weight. In the experiment, we track 386 digital cameras on Amazon for 39 months, and results show that the aspect weight for digital cameras is detected more precisely than TF-ID and HAC algorithms. The results will bridge product aspects and consumption intention to facilitate e-WOM-based marketing.

The Impact of Investors¡¯ Sentiment on the Equity Market: Evidence from Ghanaian Stock Market

OpenAIRE

Ebenezer Bennet; Lydia Obenewaa Amoako; Ricky Okine Charles; Asumadu Edward; Joseph Asante Darkwah

2012-01-01

Investor¡¯s Sentiment plays a major role in choosing which stocks we invest. Investors¡¯ sentiment can be defined as investors¡¯ attitude and opinion towards investing in the Stocks. The aim of this research is to analyse the individual investor¡¯s sentiment and also to analyse the influence of Market Specific Factors on investors¡¯ sentiment. The investor¡¯s attitude towards investing is influenced by rumours, intuition, herd behaviour among investors and media coverage of the stock. 100 inv...

Changes and Sentiment: A Longitudinal E-Mail Analysis of a Large Design Project

DEFF Research Database (Denmark)

Piccolo, Sebastiano; Wilberg, Julian; Lindemann, Udo

" in emails and study its relation to sentiment. We find that sentiment decreases when problems or changes emerge, and increases when changes are implemented successfully. We discuss the implications of our findings for research and project engineering practice, providing avenues for further work....

Dissemination Patterns and Associated Network Effects of Sentiments in Social Networks

DEFF Research Database (Denmark)

Hillmann, Robert; Trier, Matthias

2012-01-01

. The dissemination patterns analyzed in this study consist of network motifs based on triples of actors and the ties among them. These motifs are associated with common social network effects to derive meaningful insights about dissemination activities. The data basis includes several thousand social networks...... with textual messages classified according to embedded positive and negative sentiments. Based on this data, sub-networks are extracted and analyzed with a dynamic network motif analysis to determine dissemination patterns and associated network effects. Results indicate that the emergence of digital social...... networks exhibits a strong tendency towards reciprocity, followed by the dominance of hierarchy as an intermediate step leading to social clustering with hubs and transitivity effects for both positive and negative sentiments to the same extend. Sentiments embedded in exchanged textual messages do only...

NRFixer: Sentiment Based Model for Predicting the Fixability of Non-Reproducible Bugs

Directory of Open Access Journals (Sweden)

Anjali Goyal

2017-08-01

Full Text Available Software maintenance is an essential step in software development life cycle. Nowadays, software companies spend approximately 45\\% of total cost in maintenance activities. Large software projects maintain bug repositories to collect, organize and resolve bug reports. Sometimes it is difficult to reproduce the reported bug with the information present in a bug report and thus this bug is marked with resolution non-reproducible (NR. When NR bugs are reconsidered, a few of them might get fixed (NR-to-fix leaving the others with the same resolution (NR. To analyse the behaviour of developers towards NR-to-fix and NR bugs, the sentiment analysis of NR bug report textual contents has been conducted. The sentiment analysis of bug reports shows that NR bugs' sentiments incline towards more negativity than reproducible bugs. Also, there is a noticeable opinion drift found in the sentiments of NR-to-fix bug reports. Observations driven from this analysis were an inspiration to develop a model that can judge the fixability of NR bugs. Thus a framework, {NRFixer,} which predicts the probability of NR bug fixation, is proposed. {NRFixer} was evaluated with two dimensions. The first dimension considers meta-fields of bug reports (model-1 and the other dimension additionally incorporates the sentiments (model-2 of developers for prediction. Both models were compared using various machine learning classifiers (Zero-R, naive Bayes, J48, random tree and random forest. The bug reports of Firefox and Eclipse projects were used to test {NRFixer}. In Firefox and Eclipse projects, J48 and Naive Bayes classifiers achieve the best prediction accuracy, respectively. It was observed that the inclusion of sentiments in the prediction model shows a rise in the prediction accuracy ranging from 2 to 5\\% for various classifiers.

A Visualization of Evolving Clinical Sentiment Using Vector Representations of Clinical Notes.

Science.gov (United States)

Ghassemi, Mohammad M; Mark, Roger G; Nemati, Shamim

2015-09-01

Our objective in this paper was to visualize the evolution of clinical language and sentiment with respect to several common population-level categories including: time in the hospital, age, mortality, gender and race. Our analysis utilized seven years of unstructured free text notes from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) database. The text data was partitioned by category and used to generate several high dimensional vector space representations. We generated visualizations of the vector spaces using Distributed Stochastic Neighbor Embedding (tSNE) and Principal Component Analysis (PCA). We also investigated representative words from clusters in the vector space. Lastly, we inferred the general sentiment of the clinical notes toward each parameter by gauging the average distance between positive and negative keywords and all other terms in the space. We found intriguing differences in the sentiment of clinical notes over time, outcome, and demographic features. We noted a decrease in the homogeneity and complexity of clusters over time for patients with poor outcomes. We also found greater positive sentiment for females, unmarried patients, and patients of African ethnicity.

Public sentiment and movement patterns during natural hazards

Science.gov (United States)

Huang, Q.; Guo, C.

2017-12-01

Recently, we have unfortunately witnessed a series of deadly hurricane events, including Harvey, Irma, Jose, Maria and Nate. Effective disaster management actions such as getting citizen sheltered and evacuated can significantly reduce injuries and fatalities. A more comprehensive understanding of citizen's perceptions (e.g., sentiment) about a disaster and movement behaviors (e.g., evacuation) will help improve disaster management and decision making during natural hazards. With the popularity of various social media platforms (i.e. Twitter), there has been great potentials in using social media data to detect and analyze citizen's perceptions and moving behaviors before, during and after a natural hazard. Using the geo-tagged tweets generated during recent hurricane events, the study will examine the movement interactions between citizens and a hurricane and also explore citizens' tweeting behaviors and sentiments at different stages of a disaster. The results provide insights on understanding 1) spatiotemporal patterns of public movements (i.e., when and where did people's movements happen), 2) how were people's movements related to the hurricane trajectory, 3) when did people in different locations start to pay attention to the hurricane, and finally 4) how were the sentiments of people in different places towards the hurricane during different disaster stages.

Sentiment Analysis on Tweets about Diabetes: An Aspect-Level Approach

KAUST Repository

Salas-Zárate, María del Pilar

2017-02-19

In recent years, some methods of sentiment analysis have been developed for the health domain; however, the diabetes domain has not been explored yet. In addition, there is a lack of approaches that analyze the positive or negative orientation of each aspect contained in a document (a review, a piece of news, and a tweet, among others). Based on this understanding, we propose an aspect-level sentiment analysis method based on ontologies in the diabetes domain. The sentiment of the aspects is calculated by considering the words around the aspect which are obtained through N-gram methods (N-gram after, N-gram before, and N-gram around). To evaluate the effectiveness of our method, we obtained a corpus from Twitter, which has been manually labelled at aspect level as positive, negative, or neutral. The experimental results show that the best result was obtained through the N-gram around method with a precision of 81.93%, a recall of 81.13%, and an -measure of 81.24%.

Sentiment Analysis on Tweets about Diabetes: An Aspect-Level Approach

KAUST Repository

Salas-Zá rate, Marí a del Pilar; Medina-Moreira, José ; Lagos-Ortiz, Katty; Luna-Aveiga, Harry; Rodriguez-Garcia, Miguel Angel; Valencia-Garcí a, Rafael

2017-01-01

In recent years, some methods of sentiment analysis have been developed for the health domain; however, the diabetes domain has not been explored yet. In addition, there is a lack of approaches that analyze the positive or negative orientation of each aspect contained in a document (a review, a piece of news, and a tweet, among others). Based on this understanding, we propose an aspect-level sentiment analysis method based on ontologies in the diabetes domain. The sentiment of the aspects is calculated by considering the words around the aspect which are obtained through N-gram methods (N-gram after, N-gram before, and N-gram around). To evaluate the effectiveness of our method, we obtained a corpus from Twitter, which has been manually labelled at aspect level as positive, negative, or neutral. The experimental results show that the best result was obtained through the N-gram around method with a precision of 81.93%, a recall of 81.13%, and an -measure of 81.24%.

Measuring Corporate Reputation using Sentiment Analysis

DEFF Research Database (Denmark)

Colleoni, Elanor; Arvidsson, Adam; Hansen, Lars K.

and monitor reputation through the analysis of user generated content in real-time. In this paper, we show how social media content can be used to measure the online reputation of a company. Furthermore, we present an open platform that uses a sentiment analysis algorithm on twitter traffic to monitor...

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA.

Science.gov (United States)

Cao, Xiaodong; MacNaughton, Piers; Deng, Zhengyi; Yin, Jie; Zhang, Xi; Allen, Joseph G

2018-02-02

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users' sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions.

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA

Directory of Open Access Journals (Sweden)

Xiaodong Cao

2018-02-01

Full Text Available Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA, USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users’ sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions.

The predictive power of the business and bank sentiment of firms : A high-dimensional Granger causality approach

NARCIS (Netherlands)

Wilms, I.; Gelper, S.E.C.; Croux, C.

2016-01-01

We study the predictive power of industry-specific economic sentiment indicators for future macro-economic developments. In addition to the sentiment of firms towards their own business situation, we study their sentiment with respect to the banking sector – their main credit providers. The use of

Funciones de la novela sentimental hispanoamericana durante el siglo XIX

OpenAIRE

Zó, Ramiro

2007-01-01

Se analizará cómo funcionan los textos sentimentales hispanoamericanos en los lectores según dos modos de concebir la recepción de estas obras: la lectura en un “microambiente" de un lector/a sentimental-individual y la lectura en un “macroambiente" de varios lectores de novelas sentimentales. Así también, se pretende fijar las características fundamentales de la narrativa sentimental hispanoamericana en un conjunto de textos representativos de esta modalidad literaria. A su vez, este análisi...

What Can Rational Investors Do About Excessive Volatility and Sentiment Fluctuations?

OpenAIRE

Bernard Dumas; Alexander Kurshev; Raman Uppal

2005-01-01

Our objective is to understand the trading strategy that would allow an investor to take advantage of 'excessive' stock price volatility and 'sentiment' fluctuations. We construct a general equilibrium model of sentiment. In it, there are two classes of agents and stock prices are excessively volatile because one class is overconfident about a public signal. As a result, this class of irrational agents changes its expectations too often, sometimes being excessively optimistic, sometimes being...

A Survey on Sentiment Classification in Face Recognition

Science.gov (United States)

Qian, Jingyu

2018-01-01

Face recognition has been an important topic for both industry and academia for a long time. K-means clustering, autoencoder, and convolutional neural network, each representing a design idea for face recognition method, are three popular algorithms to deal with face recognition problems. It is worthwhile to summarize and compare these three different algorithms. This paper will focus on one specific face recognition problem-sentiment classification from images. Three different algorithms for sentiment classification problems will be summarized, including k-means clustering, autoencoder, and convolutional neural network. An experiment with the application of these algorithms on a specific dataset of human faces will be conducted to illustrate how these algorithms are applied and their accuracy. Finally, the three algorithms are compared based on the accuracy result.

A Sentiment-Enhanced Hybrid Recommender System for Movie Recommendation: A Big Data Analytics Framework

Directory of Open Access Journals (Sweden)

Yibo Wang

2018-01-01

Full Text Available Movie recommendation in mobile environment is critically important for mobile users. It carries out comprehensive aggregation of user’s preferences, reviews, and emotions to help them find suitable movies conveniently. However, it requires both accuracy and timeliness. In this paper, a movie recommendation framework based on a hybrid recommendation model and sentiment analysis on Spark platform is proposed to improve the accuracy and timeliness of mobile movie recommender system. In the proposed approach, we first use a hybrid recommendation method to generate a preliminary recommendation list. Then sentiment analysis is employed to optimize the list. Finally, the hybrid recommender system with sentiment analysis is implemented on Spark platform. The hybrid recommendation model with sentiment analysis outperforms the traditional models in terms of various evaluation criteria. Our proposed method makes it convenient and fast for users to obtain useful movie suggestions.

Does Sentiment Among Users in Online Social Networks Polarize or Balance Out?

DEFF Research Database (Denmark)

Trier, Matthias; Hillmann, Robert

2017-01-01

Users express and share sentiments electronically when they communicate within online social network applications. One way to analyze such interdependent data is focusing on the inter-user relationships by applying a sociological perspective based on social network analysis. Existing studies exam...... examined the existence or distribution of sentiments in online communication at a general level or in small observed groups....

Sentiments that Affect Sociopolitical Legitimation of TNCs in Bangladesh, India, and Pakistan

DEFF Research Database (Denmark)

Bakhtiar Rana, Mohammad; Sørensen, Olav Jull

2014-01-01

Our study investigates the transnational enterprises' (TNCs’) socio-political legitimization in Bangladesh, India, and Pakistan with a view to ensuring sustainability in the institutional context. We took institutional perspective as a theoretical lens, used a grounded theory method, and employed...... and patriotism,’ and ‘ecological balance’, and suggest that tensions stemming from these three sentiments can be managed and often turned into opportunities if appropriate strategies are applied. Eight types of strategies derived from the nine case studies are presented in order to mitigate, manage, and cash...... in on the REN-sentiments in South Asian markets. These strategies include collaboration strategy, local development strategy, strategy of alignment with socio-political actors, local name and staffing strategy, hibernation strategy, sentiment-focused strategy, isomorphism strategy, and openness strategy....

The relationship between SERVQUAL, national customer satisfaction indices & consumer sentiment

DEFF Research Database (Denmark)

Kristensen, Kai; Eskildsen, Jacob Kjær

2008-01-01

The focus of this study is to integrate SERVQUAL with a national customer satisfaction index in this context the EPSI Rating framework and explore the possible relationship with consumer sentiment measures. The data for this study comes from the Danish Customer Satisfaction Index 2007. Here app....... 1700 customers have evaluated their preferred bank. The questionnaire consists of two parts: the basic EPSI statement as well as 15 statements covering the 5 dimensions from SERVQUAL. Furthermore the respondents answered two questions related to consumer sentiment. The results show that both SERVQUAL...

Stigma Sentiments and Self-Meanings: Exploring the Modified Labeling Theory of Mental Illness

Science.gov (United States)

Kroska, Amy; Harkness, Sarah K.

2006-01-01

We introduce "stigma sentiments" as a way to operationalize the cultural conceptions of the mentally ill. Stigma sentiments are the evaluation, potency, and activity (EPA) associated with the cultural category "a mentally ill person." We find consistent support for the validity of the evaluation and potency components as measures of these…

Perceptions of Menthol Cigarettes Among Twitter Users: Content and Sentiment Analysis.

Science.gov (United States)

Rose, Shyanika W; Jo, Catherine L; Binns, Steven; Buenger, Melissa; Emery, Sherry; Ribisl, Kurt M

2017-02-27

Menthol cigarettes are used disproportionately by African American, female, and adolescent smokers. Twitter is also used disproportionately by minority and younger populations, providing a unique window into conversations reflecting social norms, behavioral intentions, and sentiment toward menthol cigarettes. Our purpose was to identify the content and frequency of conversations about menthol cigarettes, including themes, populations, user smoking status, other tobacco or substances, tweet characteristics, and sentiment. We also examined differences in menthol cigarette sentiment by prevalent categories, which allowed us to assess potential perceptions, misperceptions, and social norms about menthol cigarettes on Twitter. This approach can inform communication about these products, particularly to subgroups who are at risk for menthol cigarette use. Through a combination of human and machine classification, we identified 94,627 menthol cigarette-relevant tweets from February 1, 2012 to January 31, 2013 (1 year) from over 47 million tobacco-related messages gathered prospectively from the Twitter Firehose of all public tweets and metadata. Then, 4 human coders evaluated a random sample of 7000 tweets for categories, including sentiment toward menthol cigarettes. We found that 47.98% (3194/6657) of tweets expressed positive sentiment, while 40.26% (2680/6657) were negative toward menthol cigarettes. The majority of tweets by likely smokers (2653/4038, 65.70%) expressed positive sentiment, while 91.2% (320/351) of nonsmokers and 71.7% (91/127) of former smokers indicated negative views. Positive views toward menthol cigarettes were predominant in tweets that discussed addiction or craving, marijuana, smoking, taste or sensation, song lyrics, and tobacco industry or marketing or tweets that were commercial in nature. Negative views toward menthol were more common in tweets about smoking cessation, health, African Americans, women, and children and adolescents

‘Thousands of throbbing hearts' - Sentimentality and community in popular Victorian poetry: Longfellow's Evangeline and Tennyson's Enoch Arden

Directory of Open Access Journals (Sweden)

Kirstie Blair

2007-04-01

Full Text Available This essay explores the function of sentimentality in popular nineteenth-century narrative poetry by focusing on Tennyson's 'Enoch Arden' and Longfellow's 'Evangeline', two poems that have suffered relative critical neglect due to their status as sentimental verse. It argues that both texts, in their stories of exile, alienation and eventual recuperation, set up their hero and heroine as role-models for ways of feeling and use them to examine the possibility of using personal feeling as a conduit for communal sentiment. While both poems deploy the standard tropes of Victorian sentimentality, the ambiguous conclusions of 'Enoch Arden 'and 'Evangeline' , I argue, call into question the clichés of sentimental discourse. The fates of Enoch and of Evangeline offer, to some extent, a darker vision of the potential for sentimental responses to an individual's suffering to create feeling communities either within or without the poem.

Impact of Family Sentiments on Indian Woman and Their Buying Behaviour

OpenAIRE

Ramesh Babu Kakumanu; Dr. V. Israel Raju; Dr. A. Kishore Kumar

2015-01-01

A woman basically is an emotional creature and woman without emotions is like cake without cream. They undergo all types of emotions like joy, fear, anger, humor, sex, empathy and love. Family sentiments are most powerful tools to push woman into emotional state of mind. Family sentiments in the form of relationships, sharing love, caring, security, warmth, sex, and living together are frequently used in the advertisements. This article studies family appeals impact on Indian woman. The age b...

Sentiment Analysis in Geo Social Streams by using Machine Learning Techniques

OpenAIRE

Twanabasu, Bikesh

2018-01-01

Treball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi: SIW013. Curs acadèmic 2017-2018 Massive amounts of sentiment rich data are generated on social media in the form of Tweets, status updates, blog post, reviews, etc. Different people and organizations are using these user generated content for decision making. Symbolic techniques or Knowledge base approaches and Machine learning techniques are two main techniques used for analysis sentiment...

Arabic Feature-Based Level Sentiment Analysis Using Lexicon ...

African Journals Online (AJOL)

pc

2018-03-05

Mar 5, 2018 ... structured reviews being prior knowledge for mining unstructured reviews. ... FDSO has been introduced, which defines a space of product features ... polarity of a review using feature ontology and sentiment lexicons.

360-MAM-Affect: Sentiment Analysis with the Google Prediction API and EmoSenticNet

Directory of Open Access Journals (Sweden)

Eleanor Mulholland

2015-08-01

Full Text Available Online recommender systems are useful for media asset management where they select the best content from a set of media assets. We have developed an architecture for 360-MAM- Select, a recommender system for educational video content. 360-MAM-Select will utilise sentiment analysis and gamification techniques for the recommendation of media assets. 360-MAM-Select will increase user participation with digital content through improved video recommendations. Here, we discuss the architecture of 360-MAM-Select and the use of the Google Prediction API and EmoSenticNet for 360-MAM-Affect, 360-MAM-Select's sentiment analysis module. Results from testing two models for sentiment analysis, Sentiment Classifier (Google Prediction API and EmoSenticNetClassifer (Google Prediction API + EmoSenticNet are promising. Future work includes the implementation and testing of 360-MAM-Select on video data from YouTube EDU and Head Squeeze.

External validity of sentiment mining reports: Can current methods identify demographic biases, event biases, and manipulation of reviews?

NARCIS (Netherlands)

Wijnhoven, Alphonsus B.J.M.; Bloemen, Oscar

2014-01-01

Many publications in sentiment mining provide new techniques for improved accuracy in extracting features and corresponding sentiments in texts. For the external validity of these sentiment reports, i.e., the applicability of the results to target audiences, it is important to well analyze data of

The Asymmetric Predictive Effects of Investor Sentiment

DEFF Research Database (Denmark)

Lutz, Chandler

investors only act as corrective force during certain time periods. We also show that our index predicts implied volatility, media pessimism, and mutual fund flows. Overall, our findings are consistent with both the theories and anecdotal accounts of investor sentiment in the stock market....

Sentiment Analysis on Tweets about Diabetes: An Aspect-Level Approach

Directory of Open Access Journals (Sweden)

María del Pilar Salas-Zárate

2017-01-01

Full Text Available In recent years, some methods of sentiment analysis have been developed for the health domain; however, the diabetes domain has not been explored yet. In addition, there is a lack of approaches that analyze the positive or negative orientation of each aspect contained in a document (a review, a piece of news, and a tweet, among others. Based on this understanding, we propose an aspect-level sentiment analysis method based on ontologies in the diabetes domain. The sentiment of the aspects is calculated by considering the words around the aspect which are obtained through N-gram methods (N-gram after, N-gram before, and N-gram around. To evaluate the effectiveness of our method, we obtained a corpus from Twitter, which has been manually labelled at aspect level as positive, negative, or neutral. The experimental results show that the best result was obtained through the N-gram around method with a precision of 81.93%, a recall of 81.13%, and an F-measure of 81.24%.

Sentiment analysis for PTSD signals

CERN Document Server

Kagan, Vadim; Sapounas, Demetrios

2013-01-01

This book describes a computational framework for real-time detection of psychological signals related to Post-Traumatic Stress Disorder (PTSD) in online text-based posts, including blogs and web forums. Further, it explores how emerging computational techniques such as sentiment mining can be used in real-time to identify posts that contain PTSD-related signals, flag those posts, and bring them to the attention of psychologists, thus providing an automated flag and referral capability.

Sentiment Analysis in the Sales Review of Indonesian Marketplace by Utilizing Support Vector Machine

Directory of Open Access Journals (Sweden)

Anang Anggono Lutfi

2018-04-01

Full Text Available The online store is changing people’s shopping behavior. Despite the fact, the potential customer’s distrust in the quality of products and service is one of the online store’s weaknesses. A review is provided by the online stores to overcome this weakness. Customers often write a review using languages that are not well structured. Sentiment analysis is used to extract the polarity of the unstructured texts. This research attempted to do a sentiment analysis in the sales review. Sentiment analysis in sales reviews can be used as a tool to evaluate the sales. This research intends to conduct a sentiment analysis in the sales review of Indonesian marketplace by utilizing Support Vector Machine and Naive Bayes. The reviews of the data are gathered from one of Indonesian marketplace, Bukalapak. The data are classified into positive or negative class. TF-IDF is used to feature extraction. The experiment shows that Support Vector Machine with linear kernel provides higher accuracy than Naive Bayes. Support Vector Machine shows the highest accuracy average. The generated accuracy is 93.65%. This approach of sentiment analysis in sales review can be used as the base of intelligent sales evaluation for online stores in the future.

Developing resources for sentiment analysis of informal Arabic text in social media

OpenAIRE

Itani, Maher; Roast, Chris; Al-Khayatt, Samir

2017-01-01

Natural Language Processing (NLP) applications such as text categorization, machine translation, sentiment analysis, etc., need annotated corpora and lexicons to check quality and performance. This paper describes the development of resources for sentiment analysis specifically for Arabic text in social media. A distinctive feature of the corpora and lexicons developed are that they are determined from informal Arabic that does not conform to grammatical or spelling standards. We refer to Ara...

Public sentiment analysis in Twitter data for prediction of a company's stock price movements

NARCIS (Netherlands)

Li, B.; Chan, K.C.C.; Ou, C.X.J.; Li, Y.; Guo, J.

2014-01-01

There has recently been some effort to mine social media for public sentiment analysis. Studies have suggested that public emotions shown through Tweeter may well be correlated with the Dow Jones Industrial Average. However, can public sentiment be analyzed to predict the movements of the stock

Reconciliation Sentiment among Victims of Genocide in Rwanda: Conceptualizations, and Relationships with Mental Health

Science.gov (United States)

Mukashema, Immaculee; Mullet, Etienne

2010-01-01

In two studies that were conducted in Rwanda, we have examined the conceptualizations held by people who have experienced genocide with regard to reconciliation sentiment and quantitatively assessed the relationship between reconciliation sentiment and mental health. It was found that the participants have articulated conceptualizations regarding…

Sentiment Propagation in Social Networks: A Case Study in LiveJournal

Science.gov (United States)

Zafarani, Reza; Cole, William D.; Liu, Huan

Social networking websites have facilitated a new style of communication through blogs, instant messaging, and various other techniques. Through collaboration, millions of users participate in millions of discussions every day. However, it is still difficult to determine the extent to which such discussions affect the emotions of the participants. We surmise that emotionally-oriented discussions may affect a given user's general emotional bent and be reflected in other discussions he or she may initiate or participate in. It is in this way that emotion (or sentiment) may propagate through a network. In this paper, we analyze sentiment propagation in social networks, review the importance and challenges of such a study, and provide methodologies for measuring this kind of propagation. A case study has been conducted on a large dataset gathered from the LiveJournal social network. Experimental results are promising in revealing some aspects of the sentiment propagation taking place in social networks.

Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals.

Science.gov (United States)

Jung, Hyesil; Park, Hyeoun-Ae; Song, Tae-Min

2017-07-24

Social networking services (SNSs) contain abundant information about the feelings, thoughts, interests, and patterns of behavior of adolescents that can be obtained by analyzing SNS postings. An ontology that expresses the shared concepts and their relationships in a specific field could be used as a semantic framework for social media data analytics. The aim of this study was to refine an adolescent depression ontology and terminology as a framework for analyzing social media data and to evaluate description logics between classes and the applicability of this ontology to sentiment analysis. The domain and scope of the ontology were defined using competency questions. The concepts constituting the ontology and terminology were collected from clinical practice guidelines, the literature, and social media postings on adolescent depression. Class concepts, their hierarchy, and the relationships among class concepts were defined. An internal structure of the ontology was designed using the entity-attribute-value (EAV) triplet data model, and superclasses of the ontology were aligned with the upper ontology. Description logics between classes were evaluated by mapping concepts extracted from the answers to frequently asked questions (FAQs) onto the ontology concepts derived from description logic queries. The applicability of the ontology was validated by examining the representability of 1358 sentiment phrases using the ontology EAV model and conducting sentiment analyses of social media data using ontology class concepts. We developed an adolescent depression ontology that comprised 443 classes and 60 relationships among the classes; the terminology comprised 1682 synonyms of the 443 classes. In the description logics test, no error in relationships between classes was found, and about 89% (55/62) of the concepts cited in the answers to FAQs mapped onto the ontology class. Regarding applicability, the EAV triplet models of the ontology class represented about 91

Sentimentality and Nostalgia in Elderly People in Bulgaria and Greece - Cross-Validity of the Questionnaire SNEP and Cross-Cultural Comparison.

Science.gov (United States)

Stoyanova, Stanislava Yordanova; Giannouli, Vaitsa; Gergov, Teodor Krasimirov

2017-03-01

Sentimentality and nostalgia are two similar psychological constructs, which play an important role in the emotional lives of elderly people who are usually focused on the past. There are two objectives of this study - making cross-cultural comparison of sentimentality and nostalgia among Bulgarian and Greek elderly people using a questionnaire, and establishing the psychometric properties of this questionnaire among Greek elderly people. Sentimentality and nostalgia in elderly people in Bulgaria and Greece were studied by means of Sentimentality and Nostalgia in Elderly People questionnaire (SNEP), created by Gergov and Stoyanova (2013). For the Greek version, one factor structure without sub-scales is proposed, while for the Bulgarian version of SNEP the factor structure had four sub-scales, besides the total score. Together with some similarities (medium level of nostalgia and sentimentality being widespread), the elderly people in Bulgaria and Greece differed cross-culturally in their sentimentality and nostalgia related to the past in direction of more increased sentimentality and nostalgia in the Bulgarian sample. Some gender and age differences revealed that the oldest male Bulgarians were the most sentimental. The psychometric properties of this questionnaire were examined for the first time in a Greek sample of elders and a trend was found for stability of sentimentality and nostalgia in elderly people that could be studied further in longitudinal studies.

A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification

Science.gov (United States)

Wang, Suge; Li, Deyu; Wei, Yingjie; Li, Hongxia

With the rapid growth of e-commerce, product reviews on the Web have become an important information source for customers' decision making when they intend to buy some product. As the reviews are often too many for customers to go through, how to automatically classify them into different sentiment orientation categories (i.e. positive/negative) has become a research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for product review text sentiment classification. In order to validate the validity of the proposed method, we compared it with other methods respectively based on information gain and mutual information while support vector machine is adopted as the classifier. In this paper, 6 subexperiments are conducted by combining different feature selection methods with 2 kinds of candidate feature sets. Under 1006 review documents of cars, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance with F value 83.3% while the candidate features are the words which appear in both positive and negative texts.

Balancing Machine Work, Comfort Work, and Sentimental Work

DEFF Research Database (Denmark)

Pedersen, Maria Ie; Hansen, Magnus; Hertzum, Morten

2011-01-01

and attention. We investigate ambulance care in three of Denmark’s five healthcare regions, which staff ambulances with emergency medical technicians, paramedics, and physicians. Using the concept of illness trajectory we analyse how the ambulance crews balance machine work, which involves continuously...... monitoring the equipment, comfort work, which is actions taken to relieve the pain or discomfort of the patient, and sentimental work, which is care for the patient’s physical and mental well-being, often verbal in nature. The analysis shows that comfort and sentimental work often takes priority over machine...... work, but also that this has negative consequences. Equipment for use in ambulances should aim at supporting the ambulance crews in competently and dynamically balancing the different types of work and should, consequently, avoid binding the crew’s attention for unbroken periods of time....

Towards a Unified Sentiment Lexicon Based on Graphics Processing Units

Directory of Open Access Journals (Sweden)

Liliana Ibeth Barbosa-Santillán

2014-01-01

Full Text Available This paper presents an approach to create what we have called a Unified Sentiment Lexicon (USL. This approach aims at aligning, unifying, and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. One problem related to the task of the automatic unification of different scores of sentiment lexicons is that there are multiple lexical entries for which the classification of positive, negative, or neutral {P,N,Z} depends on the unit of measurement used in the annotation methodology of the source sentiment lexicon. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and −1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and −1 means they are perfectly inversely correlated and so is the UnifiedMetrics procedure for CPU and GPU, respectively. Another problem is the high processing time required for computing all the lexical entries in the unification task. Thus, the USL approach computes a subset of lexical entries in each of the 1344 GPU cores and uses parallel processing in order to unify 155802 lexical entries. The results of the analysis conducted using the USL approach show that the USL has 95.430 lexical entries, out of which there are 35.201 considered to be positive, 22.029 negative, and 38.200 neutral. Finally, the runtime was 10 minutes for 95.430 lexical entries; this allows a reduction of the time computing for the UnifiedMetrics by 3 times.

On the deep structure of social affect: Attitudes, emotions, sentiments, and the case of "contempt".

Science.gov (United States)

Gervais, Matthew M; Fessler, Daniel M T

2017-01-01

Contempt is typically studied as a uniquely human moral emotion. However, this approach has yielded inconclusive results. We argue this is because the folk affect concept "contempt" has been inaccurately mapped onto basic affect systems. "Contempt" has features that are inconsistent with a basic emotion, especially its protracted duration and frequently cold phenomenology. Yet other features are inconsistent with a basic attitude. Nonetheless, the features of "contempt" functionally cohere. To account for this, we revive and reconfigure the sentiment construct using the notion of evolved functional specialization. We develop the Attitude-Scenario-Emotion (ASE) model of sentiments, in which enduring attitudes represent others' social-relational value and moderate discrete emotions across scenarios. Sentiments are functional networks of attitudes and emotions. Distinct sentiments, including love, respect, like, hate, and fear, track distinct relational affordances, and each is emotionally pluripotent, thereby serving both bookkeeping and commitment functions within relationships. The sentiment contempt is an absence of respect; from cues to others' low efficacy, it represents them as worthless and small, muting compassion, guilt, and shame and potentiating anger, disgust, and mirth. This sentiment is ancient yet implicated in the ratcheting evolution of human ultrasocialty. The manifolds of the contempt network, differentially engaged across individuals and populations, explain the features of "contempt," its translatability, and its variable experience as "hot" or "cold," occurrent or enduring, and anger-like or disgust-like. This rapprochement between psychological anthropology and evolutionary psychology contributes both methodological and empirical insights, with broad implications for understanding the functional and cultural organization of social affect.

Contempt, like any other social affect, can be an emotion as well as a sentiment.

Science.gov (United States)

Giner-Sorolla, Roger; Fischer, Agneta H

2017-01-01

Gervais & Fessler assert that contempt is (a) not an emotion (or an attitude) but (b) a sentiment. Here, we challenge the validity and empirical basis of these two assertions, arguing that contempt, like many other emotions, can be both an emotion and a sentiment.

Contempt, like any other social affect, can be an emotion as well as a sentiment

NARCIS (Netherlands)

Giner-Sorolla, R.; Fischer, A.H.

2017-01-01

Gervais and Fessler assert that contempt is (a) not an emotion (or an attitude), but (b) a sentiment. Here, we challenge the validity and empirical basis of these two assertions, arguing that contempt, as many other emotions, can be both an emotion and sentiment.

Sentiment and Vision in Charles Dickens's A Christmas Carol and The Cricket on the Hearth

Directory of Open Access Journals (Sweden)

Heather Tilley

2007-04-01

Full Text Available This essay explores the ways in which sentimentality is manifested through the visible, and through associative functions of the eye, in two of Dickens's Christmas books of the 1840s. I situate the relationship between vision and sentiment within discourses from eighteenth-century moral philosophy, as Adam Smith's figure of the “Impartial Spectator” (of central importance to the development of ideas around sympathy is constructed mainly through the visual. I focus on two of the Christmas Books as they offer an interesting local study to test these ideas, coming at a critical juncture within the development of Dickens's own writing style, and also at an important historical moment within an investigation into Victorian sentimentality. Within Dickens's writing, sentimentality is typically associated with the exaggerated emotional portrayal of pathetic scenes (particularly the deaths of children, designed to elicit emotional responses from the reader. However, behind the hyperbole rests a concern with the self's need to take social, ethical and moral care of others, and the role of literature and art in tutoring the reader's emotional response, with the eye playing a crucial role in this act. I further explore the way in which Dickens's interest in blindness both reinforces, and points to certain disturbances, in his sentimental vision.

Sentimentality and Nostalgia in Elderly People in Bulgaria and Greece – Cross-Validity of the Questionnaire SNEP and Cross-Cultural Comparison

Science.gov (United States)

Stoyanova, Stanislava Yordanova; Giannouli, Vaitsa; Gergov, Teodor Krasimirov

2017-01-01

Sentimentality and nostalgia are two similar psychological constructs, which play an important role in the emotional lives of elderly people who are usually focused on the past. There are two objectives of this study - making cross-cultural comparison of sentimentality and nostalgia among Bulgarian and Greek elderly people using a questionnaire, and establishing the psychometric properties of this questionnaire among Greek elderly people. Sentimentality and nostalgia in elderly people in Bulgaria and Greece were studied by means of Sentimentality and Nostalgia in Elderly People questionnaire (SNEP), created by Gergov and Stoyanova (2013). For the Greek version, one factor structure without sub-scales is proposed, while for the Bulgarian version of SNEP the factor structure had four sub-scales, besides the total score. Together with some similarities (medium level of nostalgia and sentimentality being widespread), the elderly people in Bulgaria and Greece differed cross-culturally in their sentimentality and nostalgia related to the past in direction of more increased sentimentality and nostalgia in the Bulgarian sample. Some gender and age differences revealed that the oldest male Bulgarians were the most sentimental. The psychometric properties of this questionnaire were examined for the first time in a Greek sample of elders and a trend was found for stability of sentimentality and nostalgia in elderly people that could be studied further in longitudinal studies. PMID:28344678

Why Do You Spread This Message? Understanding Users Sentiment in Social Media Campaigns

OpenAIRE

Mahmud, Jalal; Gao, Huiji

2014-01-01

Twitter has been increasingly used for spreading messages about campaigns. Such campaigns try to gain followers through their Twitter accounts, influence the followers and spread messages through them. In this paper, we explore the relationship between followers sentiment towards the campaign topic and their rate of retweeting of messages generated by the campaign. Our analysis with followers of multiple social-media campaigns found statistical significant correlations between such sentiment ...

Social Robots, fiction, and sentimentality

DEFF Research Database (Denmark)

Rodogno, Raffaele

2016-01-01

in the philosophy of art and in cognitive science that attempts to solve the so called paradox of fictional emotions, i.e., the seemingly paradoxical way in which we respond emotionally to fictional or imaginary characters and events. If sentimentality were not at issue, neither would its immorality. For the sake...... argue that there are other reasons to be worried about the wide-spread use of ersatz companionship technology that have to do with the potential loss of valuable, self-defining forms of life....

Sexed Sentiments: Interdisciplinary Perspectives on Gender and Emotion

NARCIS (Netherlands)

Ruberg, W. G.; Steenbergh, K.

2011-01-01

Sexed Sentiments provides a gender perspective on the recent turn to affect in criticism. It presents new work by scholars from different disciplines working on gender and emotion, a field par excellence where an interdisciplinary focus is fruitful. This collection presents essays from disciplines

Who is more positive in private? : analyzing sentiment differences across privacy levels and demographic factors in Facebook chats and posts

NARCIS (Netherlands)

Gao, B.; Berendt, B.; Vanschoren, J.

2015-01-01

Understanding users' sentiments in social media is important in many domains, such as marketing and online applications. Is one demographic group inherently different from another? Does a group express the same sentiment both in private and public? How can we compare the sentiments of different

"When 'Bad' is 'Good'": Identifying Personal Communication and Sentiment in Drug-Related Tweets.

Science.gov (United States)

Daniulaityte, Raminta; Chen, Lu; Lamy, Francois R; Carlson, Robert G; Thirunarayan, Krishnaprasad; Sheth, Amit

2016-10-24

To harness the full potential of social media for epidemiological surveillance of drug abuse trends, the field needs a greater level of automation in processing and analyzing social media content. The objective of the study is to describe the development of supervised machine-learning techniques for the eDrugTrends platform to automatically classify tweets by type/source of communication (personal, official/media, retail) and sentiment (positive, negative, neutral) expressed in cannabis- and synthetic cannabinoid-related tweets. Tweets were collected using Twitter streaming Application Programming Interface and filtered through the eDrugTrends platform using keywords related to cannabis, marijuana edibles, marijuana concentrates, and synthetic cannabinoids. After creating coding rules and assessing intercoder reliability, a manually labeled data set (N=4000) was developed by coding several batches of randomly selected subsets of tweets extracted from the pool of 15,623,869 collected by eDrugTrends (May-November 2015). Out of 4000 tweets, 25% (1000/4000) were used to build source classifiers and 75% (3000/4000) were used for sentiment classifiers. Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machines (SVM) were used to train the classifiers. Source classification (n=1000) tested Approach 1 that used short URLs, and Approach 2 where URLs were expanded and included into the bag-of-words analysis. For sentiment classification, Approach 1 used all tweets, regardless of their source/type (n=3000), while Approach 2 applied sentiment classification to personal communication tweets only (2633/3000, 88%). Multiclass and binary classification tasks were examined, and machine-learning sentiment classifier performance was compared with Valence Aware Dictionary for sEntiment Reasoning (VADER), a lexicon and rule-based method. The performance of each classifier was assessed using 5-fold cross validation that calculated average F-scores. One-tailed t test was

Global governance and transnational financial crime: opportunities and tensions in the global anti-money laundering regime

OpenAIRE

Tsingou, Eleni

2005-01-01

This paper examines the global anti-money laundering regime, assesses its purpose and draws some conclusions with regards to its effectiveness as a tool for targeting transnational financial crime. The paper shows that targeting money laundering is presented as a means of strengthening the integrity of the financial system and tackling organised crime through a global approach, and contrasts official policies with actual (and potential) results in practice. The paper explains that at the core...

The Barbarian Invasion: Anti-Americanism in Edith Wharton's Transatlantic Marriage Novels

OpenAIRE

Olsen, Anita Storm

2014-01-01

This thesis is a study of Edith Wharton s Madame de Treymes (1907), The Custom of the Country (1913) and The Buccaneers (1938). These novels deal with transatlantic marriages in The Gilded Age and at the turn of the last century. They contain numerous incidents of Euro-American encounters and anti-American attitudes. The aim of the thesis is to show that the novels reflect anti-American sentiments that were widespread in European literature and society at the time they were set and written. T...

Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market

Science.gov (United States)

Guo, Kun; Sun, Yi; Qian, Xin

2017-03-01

With the development of the social network, the interaction between investors in stock market became more fast and convenient. Thus, investor sentiment which can influence their investment decisions may be quickly spread and magnified through the network, and to a certain extent the stock market can be affected. This paper collected the user comments data from a popular professional social networking site of China stock market called Xueqiu, then the investor sentiment data can be obtained through semantic analysis. The dynamic analysis on relationship between investor sentiment and stock market is proposed based on Thermal Optimal Path (TOP) method. The results show that the sentiment data was not always leading over stock market price, and it can be used to predict the stock price only when the stock has high investor attention.

Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI.

Science.gov (United States)

Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T

2012-10-15

Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. Copyright © 2012 Elsevier Inc. All rights reserved.

A spanner in the works? anti-politics in global health policy: Comment on "A ghost in the machine? politics in global health policy".

Science.gov (United States)

McCoy, David; Singh, Guddi

2014-08-01

The formulation of global health policy is political; and all institutions operating in the global health landscape are political. This is because policies and institutions inevitably represent certain values, reflect particular ideologies, and preferentially serve some interests over others. This may be expressed explicitly and consciously; or implicitly and unconsciously. But it's important to recognise the social and political dimension of global health policy. In some instances however, the politics of global health policy may be actively denied or obscured. This has been described in the development studies literature as a form of 'anti-politics'. In this article we describe four forms of anti-politics and consider their application to the global health sector.

Seeing the elephant: Parsimony, functionalism, and the emergent design of contempt and other sentiments.

Science.gov (United States)

Gervais, Matthew M; Fessler, Daniel M T

2017-01-01

The target article argues that contempt is a sentiment, and that sentiments are the deep structure of social affect. The 26 commentaries meet these claims with a range of exciting extensions and applications, as well as critiques. Most significantly, we reply that construction and emergence are necessary for, not incompatible with, evolved design, while parsimony requires explanatory adequacy and predictive accuracy, not mere simplicity.

The Relationship between Market Sentiment Index and Stock Rates of Return: a Panel Data Analysis

Directory of Open Access Journals (Sweden)

Claudia Emiko Yoshinaga

2012-04-01

Full Text Available This article analyzes the relationship between market sentiment and future stock rates of return. We used amethodology based on principal component analysis to create a sentiment index for the Brazilian market withdata from 1999 to 2008. The sample consisted of companies listed on BM&FBOVESPA which were groupedinto quintiles, each representing a portfolio, according to the magnitude of the following characteristics: marketvalue, total annualized risk and listing time on BM&FBOVESPA. Next, we calculated the average return of eachportfolio for every quarter. The data for the first and last quintiles were analyzed via two-factor ANOVA, usingsentiment index of the previous period (positive or negative as the main factor and each characteristic ascontrolling factors. Finally, the sentiment index was included in a panel data pricing model. The results indicatea significant and negative relationship between the market sentiment index and the future rates of return. Thesefindings suggest the existence of a reversion pattern in stock returns, meaning that after a positive sentimentperiod, the impact on subsequent stock returns is negative, and vice-versa.

Abstracts of 3. congress of global anti-nuclear alliance

International Nuclear Information System (INIS)

2000-01-01

The 3 congress of global anti-nuclear alliance was held on 18-20 May, 2000 in Astana. There were 55 reports on different aspects of nuclear disarmament; nuclear safeguards; safe operation of nuclear power plants; rehabilitation of population and lands, damaged from many-years tests in Semipalatinsk site; radiobiological monitoring of ecosystems and others presented at the congress

On the relationship between investor sentiment, VIX and trading volume.

Directory of Open Access Journals (Sweden)

Simon Man Shing So

2015-11-01

Full Text Available As noise traders affect stock market by trading, sentiment, as a signal of noise, may have relationships with trading volume. This paper explores the effect of sentiment on the stock market’s trading volume. Increase in Volatility Index (VIX can explain the percentage increase in trading volume, but only in high VIX period. Besides, higher level of VIX is likely to be associated with greater variability of trading volume. The noise traders add liquidity to the market and provide more chances for investors to time their trade as the volatility of liquidity increases. These two kinds of impact lower rational investors’ required return. The noise traders not only drive the price deviating from fundamental value, but also influence the liquidity dimensions.

SentiHealth-Cancer: A sentiment analysis tool to help detecting mood of patients in online social networks.

Science.gov (United States)

Rodrigues, Ramon Gouveia; das Dores, Rafael Marques; Camilo-Junior, Celso G; Rosa, Thierson Couto

2016-01-01

Cancer is a critical disease that affects millions of people and families around the world. In 2012 about 14.1 million new cases of cancer occurred globally. Because of many reasons like the severity of some cases, the side effects of some treatments and death of other patients, cancer patients tend to be affected by serious emotional disorders, like depression, for instance. Thus, monitoring the mood of the patients is an important part of their treatment. Many cancer patients are users of online social networks and many of them take part in cancer virtual communities where they exchange messages commenting about their treatment or giving support to other patients in the community. Most of these communities are of public access and thus are useful sources of information about the mood of patients. Based on that, Sentiment Analysis methods can be useful to automatically detect positive or negative mood of cancer patients by analyzing their messages in these online communities. The objective of this work is to present a Sentiment Analysis tool, named SentiHealth-Cancer (SHC-pt), that improves the detection of emotional state of patients in Brazilian online cancer communities, by inspecting their posts written in Portuguese language. The SHC-pt is a sentiment analysis tool which is tailored specifically to detect positive, negative or neutral messages of patients in online communities of cancer patients. We conducted a comparative study of the proposed method with a set of general-purpose sentiment analysis tools adapted to this context. Different collections of posts were obtained from two cancer communities in Facebook. Additionally, the posts were analyzed by sentiment analysis tools that support the Portuguese language (Semantria and SentiStrength) and by the tool SHC-pt, developed based on the method proposed in this paper called SentiHealth. Moreover, as a second alternative to analyze the texts in Portuguese, the collected texts were automatically translated

COMMIT at SemEval-2017 Task 5: Ontology-based Method for Sentiment Analysis of Financial Headlines

NARCIS (Netherlands)

Schouten, Kim; Frasincar, Flavius; de Jong, F.M.G.

2017-01-01

This paper describes our submission to Task 5 of SemEval 2017, Fine-Grained Sentiment Analysis on Financial Microblogs and News, where we limit ourselves to performing sentiment analysis on news headlines only (track 2). The approach presented in this paper uses a Support Vector Machine to do the

Using Social Media to Characterize Public Sentiment Toward Medical Interventions Commonly Used for Cancer Screening: An Observational Study.

Science.gov (United States)

Metwally, Omar; Blumberg, Seth; Ladabaum, Uri; Sinha, Sidhartha R

2017-06-07

Although cancer screening reduces morbidity and mortality, millions of people worldwide remain unscreened. Social media provide a unique platform to understand public sentiment toward tools that are commonly used for cancer screening. The objective of our study was to examine public sentiment toward colonoscopy, mammography, and Pap smear and how this sentiment spreads by analyzing discourse on Twitter. In this observational study, we classified 32,847 tweets (online postings on Twitter) related to colonoscopy, mammography, or Pap smears using a naive Bayes algorithm as containing positive, negative, or neutral sentiment. Additionally, we characterized the spread of sentiment on Twitter using an established model to study contagion. Colonoscopy-related tweets were more likely to express negative than positive sentiment (negative to positive ratio 1.65, 95% CI 1.51-1.80, Psocial media data provides a unique, quantitative framework to better understand the public's perception of medical interventions that are commonly used for cancer screening. Given the growing use of social media, public health interventions to improve cancer screening should use the health perceptions of the population as expressed in social network postings about tests that are frequently used for cancer screening, as well as other people they may influence with such postings. ©Omar Metwally, Seth Blumberg, Uri Ladabaum, Sidhartha R. Sinha. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 07.06.2017.

Opinion-enhanced collaborative filtering for recommender systems through sentiment analysis

Science.gov (United States)

Wang, Wei; Wang, Hongwei

2015-10-01

The motivation of collaborative filtering (CF) comes from the idea that people often get the best recommendations from someone with similar tastes. With the growing popularity of opinion-rich resources such as online reviews, new opportunities arise as we can identify the preferences from user opinions. The main idea of our approach is to elicit user opinions from online reviews, and map such opinions into preferences that can be understood by CF-based recommender systems. We divide recommender systems into two types depending on the number of product category recommended: the multiple-category recommendation and the single-category recommendation. For the former, sentiment polarity in coarse-grained manner is identified while for the latter fine-grained sentiment analysis is conducted for each product aspect. If the evaluation frequency for an aspect by a user is greater than the average frequency by all users, it indicates that the user is more concerned with that aspect. If a user's rating for an aspect is lower than the average rating by all users, he or she is much pickier than others on that aspect. Through sentiment analysis, we then build an opinion-enhanced user preference model, where the higher the similarity between user opinions the more consistent preferences between users are. Experiment results show that the proposed CF algorithm outperforms baseline methods for product recommendation in terms of accuracy and recall.

Creative participation: collective sentiment in online co-creation communities

NARCIS (Netherlands)

Lee, H.H.M.; van Dolen, W.

2015-01-01

Co-creation communities allow companies to utilize consumers’ creative thinking in the innovation process. This paper seeks to understand the role of sentiment in user co-creation. The results suggest that management style can affect the success of co-creation communities. Specific employees’

Towards an Italian Lexicon for Polarity Classification (polarITA): a Comparative Analysis of Lexical Resources for Sentiment Analysis

OpenAIRE

Hernández Farías, Delia Irazú; Laganà, Irene; Patti, Viviana; Bosco, Cristina

2018-01-01

The paper describes a preliminary study for the development of a novel lexicon for Italian sentiment analysis, i.e. where words are associated with polarity values. Given the influence of sentiment lexica on the performance of sentiment analysis systems, a methodology based on the detection and classification of errors in existing lexical resources is proposed and an extrinsic evaluation of the impact of such errors is applied. The final aim is to build a novel resource from the filtering app...

Quantifying the cross-sectional relationship between online sentiment and the skewness of stock returns

Science.gov (United States)

Shen, Dehua; Liu, Lanbiao; Zhang, Yongjie

2018-01-01

The constantly increasing utilization of social media as the alternative information channel, e.g., Twitter, provides us a unique opportunity to investigate the dynamics of the financial market. In this paper, we employ the daily happiness sentiment extracted from Twitter as the proxy for the online sentiment dynamics and investigate its association with the skewness of stock returns of 26 international stock market index returns. The empirical results show that: (1) by dividing the daily happiness sentiment into quintiles from the least to the most happiness days, the skewness of the Most-happiness subgroup is significantly larger than that of the Least-happiness subgroup. Besides, there exist significant differences in any pair of subgroups; (2) in an event study methodology, we further show that the skewness around the highest happiness days is significantly larger than the skewness around the lowest happiness days.

Sentiment Analysis of Text Guided by Semantics and Structure

NARCIS (Netherlands)

A.C. Hogenboom (Alexander)

2015-01-01

textabstractAs moods and opinions play a pivotal role in various business and economic processes, keeping track of one's stakeholders' sentiment can be of crucial importance to decision makers. Today's abundance of user-generated content allows for the automated monitoring of the opinions of many

Combining Formal Logic and Machine Learning for Sentiment Analysis

DEFF Research Database (Denmark)

Petersen, Niklas Christoffer; Villadsen, Jørgen

2014-01-01

This paper presents a formal logical method for deep structural analysis of the syntactical properties of texts using machine learning techniques for efficient syntactical tagging. To evaluate the method it is used for entity level sentiment analysis as an alternative to pure machine learning...

Suffering Daughters and Wives. Sentimental Themes in Finnish and Nordic Realism

Directory of Open Access Journals (Sweden)

Saija Isomaa

2010-10-01

Full Text Available This article examines sentimental themes and scenarios in Nordic nineteenthcentury literature, focusing on Finnish realism. The main claim of the article is that the treatment of the Woman Question in Nordic literature is thematically connected to French sentimentalism that depicted upper-class women caught in the conflict between personal freedom and familial duties. Typical scenarios were family barrier to marriage and love triangle, in which an unhappily married woman fell in love with another man. French sentimental social novels took a stance on the position of women. Similar themes and scenarios can be found in Nordic nineteenth-century novels and plays. The ‘daughter novel’ tradition from Fredrika Bremer’s The President’s Daughters (1834 to Minna Canth’s Hanna (1886 depict the sufferings of upper-class girls in patriarchal family and society. A Doll’s House (1879 by Henrik Ibsen centers on the theme of conflicting duties, depicting the moral awakening of a doll-like wife, and Papin rouva (1893, ‘The Wife of a Clergyman’ by Juhani Aho concentrates on the sufferings and moral considerations of the unhappily married Elli. The article suggests that the sentimentalist legacy informs the Nordic nineteenth-century literature and should be taken into account in the scholarship.

Money and sentiment: a psychodynamic approach to behavioral finance.

Science.gov (United States)

Mohacsy, Ildiko; Lefer, Heidi

2007-01-01

This article tackles one of the timeliest issues for both practitioners and patients today: sentiment, psychodynamics, and the stock market. Economic bubbles and crashes have occurred regularly through history -- from Holland's 17th century tulip mania, to America's 19th century railway mania, to the 1990s high-tech obsession. Though most investors regard themselves as investing rationally, few do. Instead they react collectively, buying high and selling low in crowds. Being subject to the illusion of control, they follow regressive behavior patterns and irrational, wishful thinking. They are victimized by their own emotions of hope, fear, and uncertainty. Crises happen often in economics. Indeed, the market itself may be quantified as a conglomeration of human sentiment. The relationship between magical thinking and the pictorial language of the market will be explored. Psychodynamic conceptualizations about risk and speculation are discussed, as are the interplay of affects versus judgment, rational thinking, and the knowledge of one's own capacity for stress tolerance.

Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics.

Science.gov (United States)

Ranco, Gabriele; Bordino, Ilaria; Bormetti, Giacomo; Caldarelli, Guido; Lillo, Fabrizio; Treccani, Michele

2016-01-01

The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users' behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012-2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50% of the companies such signal Granger-causes hourly price returns. Our result indicates a "wisdom-of-the-crowd" effect that allows to exploit users' activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment.

Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics.

Directory of Open Access Journals (Sweden)

Gabriele Ranco

Full Text Available The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users' behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012-2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50% of the companies such signal Granger-causes hourly price returns. Our result indicates a "wisdom-of-the-crowd" effect that allows to exploit users' activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment.

Predicting Cyber Events by Leveraging Hacker Sentiment

OpenAIRE

Deb, Ashok; Lerman, Kristina; Ferrara, Emilio

2018-01-01

Recent high-profile cyber attacks exemplify why organizations need better cyber defenses. Cyber threats are hard to accurately predict because attackers usually try to mask their traces. However, they often discuss exploits and techniques on hacking forums. The community behavior of the hackers may provide insights into groups' collective malicious activity. We propose a novel approach to predict cyber events using sentiment analysis. We test our approach using cyber attack data from 2 major ...

Can Big Data Machines Analyze Stock Market Sentiment?

Science.gov (United States)

Dhar, Vasant

2014-12-01

Do the massive amounts of social and professionally curated data on the Internet contain useful sentiment about the market that "big data machines" can extract systematically? If so, what are the important challenges in creating economic value from these diffuse sources? In this commentary, I delve into these questions and frame the challenges involved using recent market developments as an illustrative backdrop.

Toward a Critical-Sentimental Orientation in Human Rights Education

Science.gov (United States)

Zembylas, Michalinos

2016-01-01

This paper addresses one of the challenges in human rights education (HRE) concerning the conceptualization of a pedagogical orientation that avoids both the pitfalls of a purely juridical address and a "cheap sentimental" approach. The paper uses as its point of departure Richard Rorty's key intervention on human rights discourse and…

The Effect of Economic and Cultural Globalization on Anti-U.S. Transnational Terrorism 1971–2000*

Directory of Open Access Journals (Sweden)

Omar Lizardo

2015-08-01

Full Text Available The events of 9/11 have rekindled interest in the social sciences concerning the global factors responsible for transnational terrorism. Two opposing frameworks currently dominate the scene: proponents of a “destructive globalization” approach argue that processes related to the transnationalization of capital produce native resistance in the more economically disadvantaged areas of the globe that is manifested as transnational terrorist attacks, especially against the U.S., “civilizing globalization” arguments point to precisely the opposite effect: economic globalization through the spread of markets and material goods brings with it prosperity and higher living standards, thus defusing the motivation to engage in high-risk political violence. In this paper, I propose an additional framework that goes beyond the narrow realism of the destructive globalization and civilizing globalization perspectives by examining the role of the globalization of world culture in theproduction of anti-u.s. terrorism. I argue that looking at the role of world cultural structuration is important because even though economic globalization may help create local grievances outside of the most economically advantaged areas of the world, cultural globalization provides the requisite models of individual and organizational action and the interpretive schemas that “empower” local actors with the constitutive capacity to engage in high-risk acts of political violence and allows them to make local/global connections. I test this framework using time-series world-level data in order to examine the global correlates of anti-u.s. terrorist activity for the last 30 years. The results provide mixed support for both civilizing globalization and destructive globalization viewpoints. Further, and in accord with the model proposed here, cultural globalization has a positive effect on the rate of anti-u.s. terrorist activity.

Public comment sentiment on educational videos: Understanding the effects of presenter gender, video format, threading, and moderation on YouTube TED talk comments.

Directory of Open Access Journals (Sweden)

George Veletsianos

Full Text Available Scholars, educators, and students are increasingly encouraged to participate in online spaces. While the current literature highlights the potential positive outcomes of such participation, little research exists on the sentiment that these individuals may face online and on the factors that may lead some people to face different types of sentiment than others. To investigate these issues, we examined the strength of positive and negative sentiment expressed in response to TEDx and TED-Ed talks posted on YouTube (n = 655, the effect of several variables on comment and reply sentiment (n = 774,939, and the projected effects that sentiment-based moderation would have had on posted content. We found that most comments and replies were neutral in nature and some topics were more likely than others to elicit positive or negative sentiment. Videos of male presenters showed greater neutrality, while videos of female presenters saw significantly greater positive and negative polarity in replies. Animations neutralized both the negativity and positivity of replies at a very high rate. Gender and video format influenced the sentiment of replies and not just the initial comments that were directed toward the video. Finally, we found that using sentiment as a way to moderate offensive content would have a significant effect on non-offensive content. These findings have far-reaching implications for social media platforms and for those who encourage or prepare students and scholars to participate online.

Public comment sentiment on educational videos: Understanding the effects of presenter gender, video format, threading, and moderation on YouTube TED talk comments

Science.gov (United States)

Kimmons, Royce; Larsen, Ross; Dousay, Tonia A.; Lowenthal, Patrick R.

2018-01-01

Scholars, educators, and students are increasingly encouraged to participate in online spaces. While the current literature highlights the potential positive outcomes of such participation, little research exists on the sentiment that these individuals may face online and on the factors that may lead some people to face different types of sentiment than others. To investigate these issues, we examined the strength of positive and negative sentiment expressed in response to TEDx and TED-Ed talks posted on YouTube (n = 655), the effect of several variables on comment and reply sentiment (n = 774,939), and the projected effects that sentiment-based moderation would have had on posted content. We found that most comments and replies were neutral in nature and some topics were more likely than others to elicit positive or negative sentiment. Videos of male presenters showed greater neutrality, while videos of female presenters saw significantly greater positive and negative polarity in replies. Animations neutralized both the negativity and positivity of replies at a very high rate. Gender and video format influenced the sentiment of replies and not just the initial comments that were directed toward the video. Finally, we found that using sentiment as a way to moderate offensive content would have a significant effect on non-offensive content. These findings have far-reaching implications for social media platforms and for those who encourage or prepare students and scholars to participate online. PMID:29856749

Public comment sentiment on educational videos: Understanding the effects of presenter gender, video format, threading, and moderation on YouTube TED talk comments.

Science.gov (United States)

Veletsianos, George; Kimmons, Royce; Larsen, Ross; Dousay, Tonia A; Lowenthal, Patrick R

2018-01-01

Scholars, educators, and students are increasingly encouraged to participate in online spaces. While the current literature highlights the potential positive outcomes of such participation, little research exists on the sentiment that these individuals may face online and on the factors that may lead some people to face different types of sentiment than others. To investigate these issues, we examined the strength of positive and negative sentiment expressed in response to TEDx and TED-Ed talks posted on YouTube (n = 655), the effect of several variables on comment and reply sentiment (n = 774,939), and the projected effects that sentiment-based moderation would have had on posted content. We found that most comments and replies were neutral in nature and some topics were more likely than others to elicit positive or negative sentiment. Videos of male presenters showed greater neutrality, while videos of female presenters saw significantly greater positive and negative polarity in replies. Animations neutralized both the negativity and positivity of replies at a very high rate. Gender and video format influenced the sentiment of replies and not just the initial comments that were directed toward the video. Finally, we found that using sentiment as a way to moderate offensive content would have a significant effect on non-offensive content. These findings have far-reaching implications for social media platforms and for those who encourage or prepare students and scholars to participate online.

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

Science.gov (United States)

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

The Impact of an AirBnb Host's Listing Description 'Sentiment' and Length On Occupancy Rates

OpenAIRE

Martinez, Richard Diehl; Carrington, Anthony; Kuo, Tiffany; Tarhuni, Lena; Abdel-Motaal, Nour Adel Zaki

2017-01-01

There has been significant literature regarding the way product review sentiment affects brand loyalty. Intrigued by how natural language influences consumer choice, we were motivated to examine whether an AirBnb host's occupancy rate (how often their listing is booked out of the days they indicated their listing was available) can be determined by the perceived sentiment and length of their description summary. Our main goal, more generally, was to determine which features, including (but no...

Public sentiment and discourse about Zika virus on Instagram.

Science.gov (United States)

Seltzer, E K; Horst-Martz, E; Lu, M; Merchant, R M

2017-09-01

Social media have strongly influenced the awareness and perceptions of public health emergencies, and a considerable amount of social media content is now shared through images, rather than text alone. This content can impact preparedness and response due to the popularity and real-time nature of social media platforms. We sought to explore how the image-sharing platform Instagram is used for information dissemination and conversation during the current Zika outbreak. This was a retrospective review of publicly posted images about Zika on Instagram. Using the keyword '#zika' we identified 500 images posted on Instagram from May to August 2016. Images were coded by three reviewers and contextual information was collected for each image about sentiment, image type, content, audience, geography, reliability, and engagement. Of 500 images tagged with #zika, 342 (68%) contained content actually related to Zika. Of the 342 Zika-specific images, 299 were coded as 'health' and 193 were coded 'public interest'. Some images had multiple 'health' and 'public interest' codes. Health images tagged with #zika were primarily related to transmission (43%, 129/299) and prevention (48%, 145/299). Transmission-related posts were more often mosquito-human transmission (73%, 94/129) than human-human transmission (27%, 35/129). Mosquito bite prevention posts outnumbered safe sex prevention; (84%, 122/145) and (16%, 23/145) respectively. Images with a target audience were primarily aimed at women (95%, 36/38). Many posts (60%, 61/101) included misleading, incomplete, or unclear information about the virus. Additionally, many images expressed fear and negative sentiment, (79/156, 51%). Instagram can be used to characterize public sentiment and highlight areas of focus for public health, such as correcting misleading or incomplete information or expanding messages to reach diverse audiences. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights

Beliefs Underlying Messages of Anti-Cancer-Screening

Science.gov (United States)

Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Masahumi; Kato, Mio; Kiuchi, Takahiro

2018-02-26

Background: Cancer screening rates are lower in Japan than in Western countries. Meanwhile, anti-cancer-screening activists take to the internet to spread their messages that cancer screening has little or no efficacy, poses substantial health risks such as side effects from radiation exposure, and that people should forgo cancer screening. We applied a qualitative approach to explore the beliefs underlying the messages of anti-cancer-screening websites, by focusing on perceived value the beliefs provided to those who held them. Methods: We conducted online searches using Google Japan and Yahoo! Japan, targeting websites we classified as “pro,” “anti,” or “neutral” depending on their claims. We applied a dual analytic approach- inductive thematic analysis and deductive interpretative analysis- to the textual data of the anti websites. Results: Of the 88 websites analyzed, five themes that correspond to beliefs were identified: destruction of common knowledge, denial of standard cancer control, education about right cancer control, education about hidden truths, and sense of superiority that only I know the truth. Authors of anti websites ascribed two values (“safety of people” and “self-esteem”) to their beliefs. Conclusion: The beliefs of authors of anti-cancer-screening websites were supposed to be strong. It would be better to target in cancer screening promotion not outright screening refusers but screening hesitant people who are more amenable to changing their attitudes toward screening. The possible means to persuade them were discussed. Creative Commons Attribution License

Integrating sentiment analysis and term associations with geo-temporal visualizations on customer feedback streams

Science.gov (United States)

Hao, Ming; Rohrdantz, Christian; Janetzko, Halldór; Keim, Daniel; Dayal, Umeshwar; Haug, Lars-Erik; Hsu, Mei-Chun

2012-01-01

Twitter currently receives over 190 million tweets (small text-based Web posts) and manufacturing companies receive over 10 thousand web product surveys a day, in which people share their thoughts regarding a wide range of products and their features. A large number of tweets and customer surveys include opinions about products and services. However, with Twitter being a relatively new phenomenon, these tweets are underutilized as a source for determining customer sentiments. To explore high-volume customer feedback streams, we integrate three time series-based visual analysis techniques: (1) feature-based sentiment analysis that extracts, measures, and maps customer feedback; (2) a novel idea of term associations that identify attributes, verbs, and adjectives frequently occurring together; and (3) new pixel cell-based sentiment calendars, geo-temporal map visualizations and self-organizing maps to identify co-occurring and influential opinions. We have combined these techniques into a well-fitted solution for an effective analysis of large customer feedback streams such as for movie reviews (e.g., Kung-Fu Panda) or web surveys (buyers).

Global warming -- Science and anti-science

Energy Technology Data Exchange (ETDEWEB)

Preining, O. [Univ. of Vienna, Wien (Austria). Inst. for Experimental Physics]|[Austrian Academy of Sciences, Wien (Austria). Clean Air Commission

1995-06-01

The global warming debate has sparked many facts activities in almost all sectors of human endeavors. There are the hard facts, the measurements of the greenhouse gases, the statistics of human activities responsible for emissions, the demographic figures. There are the soft facts, the interpretations of the hard facts requiring additional assumptions. There are the media, the press, television, for whom environmental problems make good stories, these can be used to rise emotions, to make heroes and antiheroes. There are politicians, the global warming debate can be used even in electron campaigns. Global warming is a topic within and beyond science. The judgment (and hence use) of scientific facts is overwhelmingly influenced by the ``Weltbild`` (underlying beliefs how the world operates), and consequently opposing positions of well-known scientists arise. There are the attempts to invent futures of man on Earth: policies, regulations, laws on nation, international, and global levels shall facilitate a change in the basic behavior of all men. The global warming issue has many facets and cannot be successfully discussed without including, e.g., the North-South dialogue, world population, etc.

Talking about Climate Change and Global Warming

Science.gov (United States)

Kim, Ji Yoon; Joo, Gea-Jae

2015-01-01

The increasing prevalence of social networks provides researchers greater opportunities to evaluate and assess changes in public opinion and public sentiment towards issues of social consequence. Using trend and sentiment analysis is one method whereby researchers can identify changes in public perception that can be used to enhance the development of a social consciousness towards a specific public interest. The following study assessed Relative search volume (RSV) patterns for global warming (GW) and Climate change (CC) to determine public knowledge and awareness of these terms. In conjunction with this, the researchers looked at the sentiment connected to these terms in social media networks. It was found that there was a relationship between the awareness of the information and the amount of publicity generated around the terminology. Furthermore, the primary driver for the increase in awareness was an increase in publicity in either a positive or a negative light. Sentiment analysis further confirmed that the primary emotive connections to the words were derived from the original context in which the word was framed. Thus having awareness or knowledge of a topic is strongly related to its public exposure in the media, and the emotional context of this relationship is dependent on the context in which the relationship was originally established. This has value in fields like conservation, law enforcement, or other fields where the practice can and often does have two very strong emotive responses based on the context of the problems being examined. PMID:26418127

Talking about Climate Change and Global Warming.

Science.gov (United States)

Lineman, Maurice; Do, Yuno; Kim, Ji Yoon; Joo, Gea-Jae

2015-01-01

The increasing prevalence of social networks provides researchers greater opportunities to evaluate and assess changes in public opinion and public sentiment towards issues of social consequence. Using trend and sentiment analysis is one method whereby researchers can identify changes in public perception that can be used to enhance the development of a social consciousness towards a specific public interest. The following study assessed Relative search volume (RSV) patterns for global warming (GW) and Climate change (CC) to determine public knowledge and awareness of these terms. In conjunction with this, the researchers looked at the sentiment connected to these terms in social media networks. It was found that there was a relationship between the awareness of the information and the amount of publicity generated around the terminology. Furthermore, the primary driver for the increase in awareness was an increase in publicity in either a positive or a negative light. Sentiment analysis further confirmed that the primary emotive connections to the words were derived from the original context in which the word was framed. Thus having awareness or knowledge of a topic is strongly related to its public exposure in the media, and the emotional context of this relationship is dependent on the context in which the relationship was originally established. This has value in fields like conservation, law enforcement, or other fields where the practice can and often does have two very strong emotive responses based on the context of the problems being examined.

Sentiment Analysis Based on Psychological and Linguistic Features for Spanish Language

KAUST Repository

Salas-Zá rate, Marí a Pilar; Paredes-Valverde, Mario André s; Rodriguez-Garcia, Miguel Angel; Valencia-Garcí a, Rafael; Alor-Herná ndez, Giner

2017-01-01

in the Social Media (e.g. forums, blogs, and social networks) concerning to users’ opinions about experiences buying products and hiring services. Sentiment analysis or opinion mining is the field of study that analyses people’s opinions and mood from written

#europehappinessmap: A Framework for Multi-Lingual Sentiment Analysis via Social Media Big Data (A Twitter Case Study

Directory of Open Access Journals (Sweden)

Mustafa Coşkun

2018-04-01

Full Text Available The growth and popularity of social media platforms have generated a new social interaction environment thus a new collaboration and communication network among individuals. These platforms own tremendous amount of data about users’ behaviors and sentiments since people create, share or exchange their information, ideas, pictures or video using them. One of these popular platforms is Twitter, which via its voluntary information sharing structure, provides researchers data potential of benefit for their studies. Based on Twitter data, in this study a multilingual sentiment detection framework is proposed to compute European Gross National Happiness (GNH. This framework consists of a novel data collection, filtering and sampling method, and a newly constructed multilingual sentiment detection algorithm for social media big data, and tested with nine European countries (United Kingdom, Germany, Sweden, Turkey, Portugal, The Netherlands, Italy, France and Spain and their national languages over a six year period. The reliability of the data is checked with peak/troughs comparison for special days from Wikipedia news lists. The validity is checked with a group of correlation analyses with OECD Life Satisfaction survey reports’, Euro-Dollar and other currency exchanges, and national stock market time series data. After validity and reliability confirmations, the European GNH map is drawn for six years. The main problem addressed is to propose a novel multilingual social media sentiment analysis framework for calculating GNH for countries and change the way of OECD type organizations’ survey and interview methodology. Also, it is believed that this framework can serve more detailed results (e.g., daily or hourly sentiments of society in different languages.

Large-scale Comparative Sentiment Analysis of News Articles

OpenAIRE

Wanner, Franz; Rohrdantz, Christian; Mansmann, Florian; Stoffel, Andreas; Oelke, Daniela; Krstajic, Milos; Keim, Daniel; Luo, Dongning; Yang, Jing; Atkinson, Martin

2009-01-01

Online media offers great possibilities to retrieve more news items than ever. In contrast to these technical developments, human capabilities to read all these news items have not increased likewise. To bridge this gap, this poster presents a visual analytics tool for conducting semi-automatic sentiment analysis of large news feeds. The tool retrieves and analyzes the news of two categories (Terrorist Attack and Natural Disasters) and news which belong to both categories of the Europe Media ...

Assessing sentiment in conflict zones through social media

OpenAIRE

Bourret, Andrew K.; Wines, Joshua D.; Mendes, Jason M.

2016-01-01

Approved for public release; distribution is unlimited While it is widely accepted that polling can assess levels of popular support in a geographic area by surveying a cross-segment of its population, it is less well accepted that analysts can use social media analysis to assess sentiment or popular support within the same space. We examine this question by comparing geographically anchored polling and social media data, utilizing over 1.4 million geo-referenced messages sent through the ...

Investor Sentiment and Corporate Finance: Micro and Macro

OpenAIRE

Owen A. Lamont; Jeremy C. Stein

2006-01-01

We document that net equity issuance is considerably more sensitive to aggregate stock returns and Q's than to firm-level stock returns and Q's. Very similar patterns also emerge when we look at merger activity. In light of earlier work (Campbell 1991, Vuolteenaho 2002) which finds that aggregate stock returns are less informative about future cashflows than are firm-level stock returns--and thus, potentially more strongly influenced by investor sentiment--these results suggest that both equi...

What determines the exchange rate: economic factors or market sentiment?

OpenAIRE

Gregory P. Hopper

1997-01-01

Do economic factors influence exchange rates? Or does market sentiment play a bigger role? Are short-run exchange rates predictable? Greg Hopper reviews exchange-rate economics, focusing on what is predictable and what isn't. He also examines the practical implications of exchange-rate theories for currency option pricing, risk management, and portfolio selection.

Two kinds of respect for two kinds of contempt: Why contempt can be both a sentiment and an emotion.

Science.gov (United States)

Cova, Florian; Deonna, Julien; Sander, David; Teroni, Fabrice

2017-01-01

Gervais & Fessler argue that because contempt is a sentiment, it cannot be an emotion. However, like many affective labels, it could be that "contempt" refers both to a sentiment and to a distinct emotion. This possibility is made salient by the fact that contempt can be defined by contrast with respect, but that there are different kinds of respect.

Sentiment analysis to determine the impact of online messages on smokers' choices to use varenicline.

Science.gov (United States)

Cobb, Nathan K; Mays, Darren; Graham, Amanda L

2013-12-01

Social networks are a prominent component of online smoking cessation interventions. This study applied sentiment analysis-a data processing technique that codes textual data for emotional polarity-to examine how exposure to messages about the cessation drug varenicline affects smokers' decision making around its use. Data were from QuitNet, an online social network dedicated to smoking cessation and relapse prevention. Self-reported medication choice at registration and at 30 days was coded among new QuitNet registrants who participated in at least one forum discussion mentioning varenicline between January 31, 2005 and March 9, 2008. Commercially available software was used to code the sentiment of forum messages mentioning varenicline that occurred during this time frame. Logistic regression analyses examined whether forum message exposure predicted medication choice. The sample of 2132 registrants comprised mostly women (78.3%), white participants (83.4%), averaged 41.2 years of age (SD = 10.9), and smoked on average 21.5 (SD = 9.7) cigarettes/day. After adjusting for potential confounders, as exposure to positive varenicline messages outweighed negative messages, the odds of switching to varenicline (odds ratio = 2.05, 95% confidence interval = 1.66 to 2.54) and continuing to use varenicline (odds ratio = 2.46, 95% confidence interval = 1.96 to 3.10) statistically significantly increased. Sentiment analysis is a useful tool for analyzing text-based data to examine their impact on behavior change. Greater exposure to positive sentiment in online conversations about varenicline is associated with a greater likelihood that smokers will choose to use varenicline in a quit attempt.

Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques.

Science.gov (United States)

Dashtipour, Kia; Poria, Soujanya; Hussain, Amir; Cambria, Erik; Hawalah, Ahmad Y A; Gelbukh, Alexander; Zhou, Qiang

With the advent of Internet, people actively express their opinions about products, services, events, political parties, etc., in social media, blogs, and website comments. The amount of research work on sentiment analysis is growing explosively. However, the majority of research efforts are devoted to English-language data, while a great share of information is available in other languages. We present a state-of-the-art review on multilingual sentiment analysis. More importantly, we compare our own implementation of existing approaches on common data. Precision observed in our experiments is typically lower than the one reported by the original authors, which we attribute to the lack of detail in the original presentation of those approaches. Thus, we compare the existing works by what they really offer to the reader, including whether they allow for accurate implementation and for reliable reproduction of the reported results.

The Disappearing Intellectual in the Age of Economic Darwinism

Science.gov (United States)

Giroux, Henry A.

2011-01-01

Anti-intellectualism and political illiteracy are sweeping across the American media and cultural landscape, giving rise to discourses that are unabashedly nativist, racist, and reactionary. Populist sentiments drive the rabid individualism and anti-government rhetoric of right-wing groups such as the Tea Party movement. Underlying these…

A qualitative analysis of the beliefs of Japanese anti-influenza vaccination website authors.

Science.gov (United States)

Okuhara, Tsuyoshi; Ishikawa, Hirono; Kato, Mio; Okada, Masafumi; Kiuchi, Takahiro

2018-04-01

Influenza vaccine coverage among the Japanese population is less than optimal. Anti-vaccination sentiment exists worldwide, and Japan is no exception. Anti-influenza vaccination activists argue on the internet that influenza vaccine has little or no efficacy and a high risk of side effects, and they warn that people should forgo vaccination. We conducted a qualitative analysis to explore beliefs underlying the messages of anti-influenza vaccination websites, by focusing on the perceived value these beliefs provide to those who hold them. We conducted online searches in January 2017 using two major Japanese search engines (Google Japan and Yahoo! Japan). Targeted websites were classified as "pro", "anti", or "neutral" depending on their claims. We applied a dual analytic approach-inductive thematic analysis and deductive interpretative analysis-to textual data of the anti websites. Of the 113 anti websites, we identified two themes that correspond to beliefs: it is necessary to 1) protect others against risks and exploitation related to influenza vaccination, and 2) educate others about hidden truths and self-determination. Authors of anti websites ascribed two values (people's "safety" and one's own "self-esteem") to their beliefs. Website authors may engage in anti-vaccination activities because they want to feel they are virtuous, saving people from harm caused by vaccination, and to boost their self-esteem, thinking "I am enlightening uninformed people." The anti-vaccination beliefs of website authors were considered to be strong. In promoting vaccination, it would be better not to target outright vaccine refusers, such as the authors of anti-vaccination websites; it is preferable to target vaccine-hesitant people who are more amenable to changing their attitudes toward vaccination. We discuss possible means of promoting vaccination in that target population.

Sentiment Analysis per analizzare gli effetti del cinema sulla percezione dei luoghi. Il caso pugliese / Sentiment Analysis to study the effects of cinema on the perception of places. The case of Puglia Region

Directory of Open Access Journals (Sweden)

Valentina Albanese

2016-05-01

Full Text Available Il film induced iourism è un fenomeno ormai indiscutibile e che va affrontato con sistematicità e metodologie sempre più raffinate per consentire ai policy makers di sfruttarne più consapevolmente le potenzialità. In Puglia la realizzazione di pellicole di successo ha provocato effetti turistici e territoriali notevoli. Per poter comprendere realmente se e quanto l’incoming turistico pugliese sia influenzato, nella sua dimensione quantitativa e qualitativa, dall’immagine veicolata dal cinema, si ipotizza qui l’utilizzo di una nuova metodologia di analisi: la Sentiment Analysis. Si intende passare al setaccio i Big Data tematici, tramite una scansione intelligente dei social network e poi riportare le valutazioni (sentiment sul territorio pugliese espresse nei diversi luoghi virtuali di conversazione da parte della domanda turistica. Questa tipologia di studio del dato è del tutto innovativa per il settore cineturistico e può portare ad esiti del tutto inattesi sovvertendo in alcuni casi le interpretazioni prettamente soggettive dei dati quantitativi più tradizionali. Film induced tourism is an undeniable phenomenon and it is necessary to study it sistematically and with sophisticated methods to allow policy makers to exploit, more consciously, its potentiality. In Apulia the successful movies maybe have caused tourism and territorial remarkable effects. In order to understand if and how incoming in Apulia is influenced, in quantitative and qualitative terms, from the image conveyed by cinema, we’ll use a new method of analysis: the Sentiment Analysis. It means making an intelligent scanning of social networks and then bring feedback (sentiment about Apulia expressed in different virtual places of conversation by the tourist demand. This kind of opinion mining study is totally innovative for film induced tourism and can lead to outcomes completely unexpected subverting, in some cases, subjective interpretations of the

Mechanisms Underlying the Anti-Aging and Anti-Tumor Effects of Lithocholic Bile Acid

Directory of Open Access Journals (Sweden)

Anthony Arlia-Ciommo

2014-09-01

Full Text Available Bile acids are cholesterol-derived bioactive lipids that play essential roles in the maintenance of a heathy lifespan. These amphipathic molecules with detergent-like properties display numerous beneficial effects on various longevity- and healthspan-promoting processes in evolutionarily distant organisms. Recent studies revealed that lithocholic bile acid not only causes a considerable lifespan extension in yeast, but also exhibits a substantial cytotoxic effect in cultured cancer cells derived from different tissues and organisms. The molecular and cellular mechanisms underlying the robust anti-aging and anti-tumor effects of lithocholic acid have emerged. This review summarizes the current knowledge of these mechanisms, outlines the most important unanswered questions and suggests directions for future research.

Smart Agents and Sentiment in the Heterogeneous Agent Model

Czech Academy of Sciences Publication Activity Database

Vácha, Lukáš; Baruník, Jozef; Vošvrda, Miloslav

-, č. 81 (2010), s. 39-40 ISSN 0926-4981 R&D Projects: GA ČR(CZ) GA402/09/0965; GA ČR GP402/08/P207 Grant - others:GAUK(CZ) GAUK 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : Smart traders * price movements * smart traders concept Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2010/E/vacha- smart agent s and sentiment in the heterogeneous agent model.pdf

A qualitative analysis of the beliefs of Japanese anti-influenza vaccination website authors

Directory of Open Access Journals (Sweden)

Tsuyoshi Okuhara

2018-04-01

Full Text Available Background: Influenza vaccine coverage among the Japanese population is less than optimal. Anti-vaccination sentiment exists worldwide, and Japan is no exception. Anti-influenza vaccination activists argue on the internet that influenza vaccine has little or no efficacy and a high risk of side effects, and they warn that people should forgo vaccination. We conducted a qualitative analysis to explore beliefs underlying the messages of anti-influenza vaccination websites, by focusing on the perceived value these beliefs provide to those who hold them. Methods: We conducted online searches in January 2017 using two major Japanese search engines (Google Japan and Yahoo! Japan. Targeted websites were classified as “pro”, “anti”, or “neutral” depending on their claims. We applied a dual analytic approach—inductive thematic analysis and deductive interpretative analysis—to textual data of the anti websites. Results: Of the 113 anti websites, we identified two themes that correspond to beliefs: it is necessary to 1 protect others against risks and exploitation related to influenza vaccination, and 2 educate others about hidden truths and self-determination. Authors of anti websites ascribed two values (people's “safety” and one's own “self-esteem” to their beliefs. Discussion: Website authors may engage in anti-vaccination activities because they want to feel they are virtuous, saving people from harm caused by vaccination, and to boost their self-esteem, thinking “I am enlightening uninformed people.” The anti-vaccination beliefs of website authors were considered to be strong. In promoting vaccination, it would be better not to target outright vaccine refusers, such as the authors of anti-vaccination websites; it is preferable to target vaccine-hesitant people who are more amenable to changing their attitudes toward vaccination. We discuss possible means of promoting vaccination in that target population. Keywords

Web Conversations About Complementary and Alternative Medicines and Cancer: Content and Sentiment Analysis

Science.gov (United States)

Truccolo, Ivana; Antonini, Marialuisa; Rinaldi, Fabio; Omero, Paolo; Ferrarin, Emanuela; De Paoli, Paolo; Tasso, Carlo

2016-01-01

Background The use of complementary and alternative medicine (CAM) among cancer patients is widespread and mostly self-administrated. Today, one of the most relevant topics is the nondisclosure of CAM use to doctors. This general lack of communication exposes patients to dangerous behaviors and to less reliable information channels, such as the Web. The Italian context scarcely differs from this trend. Today, we are able to mine and analyze systematically the unstructured information available in the Web, to get an insight of people’s opinions, beliefs, and rumors concerning health topics. Objective Our aim was to analyze Italian Web conversations about CAM, identifying the most relevant Web sources, therapies, and diseases and measure the related sentiment. Methods Data have been collected using the Web Intelligence tool ifMONITOR. The workflow consisted of 6 phases: (1) eligibility criteria definition for the ifMONITOR search profile; (2) creation of a CAM terminology database; (3) generic Web search and automatic filtering, the results have been manually revised to refine the search profile, and stored in the ifMONITOR database; (4) automatic classification using the CAM database terms; (5) selection of the final sample and manual sentiment analysis using a 1-5 score range; (6) manual indexing of the Web sources and CAM therapies type retrieved. Descriptive univariate statistics were computed for each item: absolute frequency, percentage, central tendency (mean sentiment score [MSS]), and variability (standard variation σ). Results Overall, 212 Web sources, 423 Web documents, and 868 opinions have been retrieved. The overall sentiment measured tends to a good score (3.6 of 5). Quite a high polarization in the opinions of the conversation partaking emerged from standard variation analysis (σ≥1). In total, 126 of 212 (59.4%) Web sources retrieved were nonhealth-related. Facebook (89; 21%) and Yahoo Answers (41; 9.7%) were the most relevant. In total, 94 CAM

Web Conversations About Complementary and Alternative Medicines and Cancer: Content and Sentiment Analysis.

Science.gov (United States)

Mazzocut, Mauro; Truccolo, Ivana; Antonini, Marialuisa; Rinaldi, Fabio; Omero, Paolo; Ferrarin, Emanuela; De Paoli, Paolo; Tasso, Carlo

2016-06-16

The use of complementary and alternative medicine (CAM) among cancer patients is widespread and mostly self-administrated. Today, one of the most relevant topics is the nondisclosure of CAM use to doctors. This general lack of communication exposes patients to dangerous behaviors and to less reliable information channels, such as the Web. The Italian context scarcely differs from this trend. Today, we are able to mine and analyze systematically the unstructured information available in the Web, to get an insight of people's opinions, beliefs, and rumors concerning health topics. Our aim was to analyze Italian Web conversations about CAM, identifying the most relevant Web sources, therapies, and diseases and measure the related sentiment. Data have been collected using the Web Intelligence tool ifMONITOR. The workflow consisted of 6 phases: (1) eligibility criteria definition for the ifMONITOR search profile; (2) creation of a CAM terminology database; (3) generic Web search and automatic filtering, the results have been manually revised to refine the search profile, and stored in the ifMONITOR database; (4) automatic classification using the CAM database terms; (5) selection of the final sample and manual sentiment analysis using a 1-5 score range; (6) manual indexing of the Web sources and CAM therapies type retrieved. Descriptive univariate statistics were computed for each item: absolute frequency, percentage, central tendency (mean sentiment score [MSS]), and variability (standard variation σ). Overall, 212 Web sources, 423 Web documents, and 868 opinions have been retrieved. The overall sentiment measured tends to a good score (3.6 of 5). Quite a high polarization in the opinions of the conversation partaking emerged from standard variation analysis (σ≥1). In total, 126 of 212 (59.4%) Web sources retrieved were nonhealth-related. Facebook (89; 21%) and Yahoo Answers (41; 9.7%) were the most relevant. In total, 94 CAM therapies have been retrieved. Most

Echoing Sentiments: Art and Melancholy in the Work of Pleshette DeArmitt

Directory of Open Access Journals (Sweden)

Michael Naas

2015-12-01

Full Text Available During those first few days, those first few weeks, truth be told, still today, something in me has wanted simply to echo the sentiments of others. That’s because I myself didn’t know exactly what to say and, truth be told, I still don’t know today. But it’s also because others, including and especially some of the people here today, beginning with my co-panelists and, perhaps especially, early on, Leigh Johnson, knew at the time just what had to be said and so expressed so well the sentiments that we all—that I at least—just wanted to echo. Just to echo, that’s what I wanted to do, because by echoing the sentiments of others I would be able to protect myself just a bit longer, I thought, though also, I self-justified, by echoing others I would be able to give back in some way to Pleshette herself, who showed us in her work that Echo does not simply repeat but initiates even when it looks or sounds as if she is not, Echo who gives back even when it sounds as if she has nothing to give, Echo who not only has her own Narcissus but her own narcissism—which Pleshette would have been the first to tell us is not only not a bad thing but a necessary one, and perhaps just what is needed for a new thinking of empathy, of mourning, and, perhaps, as I will try to say, of the ephemeral.

Digital Health Communication and Global Public Influence: A Study of the Ebola Epidemic.

Science.gov (United States)

Roberts, Hal; Seymour, Brittany; Fish, Sands Alden; Robinson, Emily; Zuckerman, Ethan

2017-01-01

Scientists and health communication professionals expressed frustration over the relationship between misinformation circulating on the Internet and global public perceptions of and responses to the Ebola epidemic originating in West Africa. Using the big data platform Media Cloud, we analyzed all English-language stories about keyword "Ebola" published from 1 July 2014 to 17 November 2014 from the media sets U.S. Mainstream Media, U.S. Regional Media, U.S. Political Blogs, U.S. Popular Blogs, Europe Media Monitor, and Global Voices to understand how social network theory and models of the networked global public may have contributed to health communication efforts. 109,400 stories met our inclusion criteria. The CDC and WHO were the two media sources with the most inlinks (hyperlinks directed to their sites). Twitter was fourth Significantly more public engagement on social media globally was directed toward stories about risks of U.S. domestic Ebola infections than toward stories focused on Ebola infections in West Africa or on science-based information. Corresponding public sentiments about Ebola were reflected in the policy responses of the international community, including violations of the International Health Regulations and the treatment of potentially exposed individuals. The digitally networked global public may have influenced the discourse, sentiment, and response to the Ebola epidemic.

Artificial Neural Network methods applied to sentiment analysis

OpenAIRE

Ebert, Sebastian

2017-01-01

Sentiment Analysis (SA) is the study of opinions and emotions that are conveyed by text. This field of study has commercial applications for example in market research (e.g., “What do customers like and dislike about a product?”) and consumer behavior (e.g., “Which book will a customer buy next when he wrote a positive review about book X?”). A private person can benefit from SA by automatic movie or restaurant recommendations, or from applications on the computer or smart phone that adapt to...

Investigating Online Destination Images Using a Topic-Based Sentiment Analysis Approach

Directory of Open Access Journals (Sweden)

Gang Ren

2017-09-01

Full Text Available With the development of Web 2.0, many studies have tried to analyze tourist behavior utilizing user-generated contents. The primary purpose of this study is to propose a topic-based sentiment analysis approach, including a polarity classification and an emotion classification. We use the Latent Dirichlet Allocation model to extract topics from online travel review data and analyze the sentiments and emotions for each topic with our proposed approach. The top frequent words are extracted for each topic from online reviews on Ctrip.com. By comparing the relative importance of each topic, we conclude that many tourists prefer to provide “suggestion” reviews. In particular, we propose a new approach to classify the emotions of online reviews at the topic level utilizing an emotion lexicon, focusing on specific emotions to analyze customer complaints. The results reveal that attraction “management” obtains most complaints. These findings may provide useful insights for the development of attractions and the measurement of online destination image. Our proposed method can be used to analyze reviews from many online platforms and domains.

Sentiments, Attitudes, and Concerns about Inclusion: Early Years in Teacher Education Programs

Science.gov (United States)

Cansiz, Mustafa; Cansiz, Nurcan

2018-01-01

This study aims to examine preservice teachers' sentiments toward students with special needs, attitudes, and concerns about inclusive education in terms of a number of demographic variables. These demographics included major area, grade level, gender, interaction with disabled people, training for inclusive education, self-confidence for teaching…

Using Sentence-Level Classifiers for Cross-Domain Sentiment Analysis

Science.gov (United States)

2014-09-01

National Defence, 2014 © Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2014 DRDC-RDDC...domain sentiment classification via spectral feature alignment. In Proceedings of the 19th international conference on World Wide Web, WWW ’10...Dennis, S. 5. DATE OF PUBLICATION (Month and year of publication of document.) September 2014 6a. NO. OF PAGES (Total containing information

Smart Agents and Sentiment in the Heterogeneous Agent Model

Czech Academy of Sciences Publication Activity Database

Vácha, Lukáš; Baruník, Jozef; Vošvrda, Miloslav

2009-01-01

Roč. 18, č. 3 (2009), s. 209-219 ISSN 1210-0455 R&D Projects: GA MŠk(CZ) LC06075; GA ČR GP402/08/P207; GA ČR(CZ) GA402/09/0965 Institutional research plan: CEZ:AV0Z10750506 Keywords : heterogeneous agent model * market structure * smart traders * Hurst exponent Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2009/E/vacha- smart agent s and sentiment in the heterogeneous agent model.pdf

Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ₁ Regularization.

Science.gov (United States)

Hernandez-Suarez, Aldo; Sanchez-Perez, Gabriel; Toscano-Medina, Karina; Martinez-Hernandez, Victor; Perez-Meana, Hector; Olivares-Mercado, Jesus; Sanchez, Victor

2018-04-29

In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events. Cyber-attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber-attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ 1 regularization.

Forecasting ability of the investor sentiment endurance index: The case of oil service stock returns and crude oil prices

International Nuclear Information System (INIS)

He, Ling T.; Casey, K.M.

2015-01-01

Using a binomial probability distribution model this paper creates an endurance index of oil service investor sentiment. The index reflects the probability of the high or low stock price being the close price for the PHLX Oil Service Sector Index. Results of this study reveal the substantial forecasting ability of the sentiment endurance index. Monthly and quarterly rolling forecasts of returns of oil service stocks have an overall accuracy as high as 52% to 57%. In addition, the index shows decent forecasting ability on changes in crude oil prices, especially, WTI prices. The accuracy of 6-quarter rolling forecasts is 55%. The sentiment endurance index, along with the procedure of true forecasting and accuracy ratio, applied in this study provides investors and analysts of oil service sector stocks and crude oil prices as well as energy policy-makers with effective analytical tools

Online Influence and Sentiment of Fitness Tweets: Analysis of Two Million Fitness Tweets.

Science.gov (United States)

Vickey, Theodore; Breslin, John G

2017-10-31

Publicly available fitness tweets may provide useful and in-depth insights into the real-time sentiment of a person's physical activity and provide motivation to others through online influence. The goal of this experimental approach using the fitness Twitter dataset is two-fold: (1) to determine if there is a correlation between the type of activity tweet (either workout or workout+, which contains the same information as a workout tweet but has additional user-generated information), gender, and one's online influence as measured by Klout Score and (2) to examine the sentiment of the activity-coded fitness tweets by looking at real-time shared thoughts via Twitter regarding their experiences with physical activity and the associated mobile fitness app. The fitness tweet dataset includes demographic and activity data points, including minutes of activity, Klout Score, classification of each fitness tweet, the first name of each fitness tweet user, and the tweet itself. Gender for each fitness tweet user was determined by a first name comparison with the US Social Security Administration database of first names and gender. Over 184 days, 2,856,534 tweets were collected in 23 different languages. However, for the purposes of this study, only the English-language tweets were analyzed from the activity tweets, resulting in a total of 583,252 tweets. After assigning gender to Twitter usernames based on the Social Security Administration database of first names, analysis of minutes of activity by both gender and Klout influence was determined. The mean Klout Score for those who shared their workout data from within four mobile apps was 20.50 (13.78 SD), less than the general Klout Score mean of 40, as was the Klout Score at the 95th percentile (40 vs 63). As Klout Score increased, there was a decrease in the number of overall workout+ tweets. With regards to sentiment, fitness-related tweets identified as workout+ reflected a positive sentiment toward physical activity

Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ1 Regularization

Science.gov (United States)

Sanchez-Perez, Gabriel; Toscano-Medina, Karina; Martinez-Hernandez, Victor; Olivares-Mercado, Jesus; Sanchez, Victor

2018-01-01

In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events. Cyber-attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber-attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ1 regularization. PMID:29710833

Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ1 Regularization

Directory of Open Access Journals (Sweden)

Aldo Hernandez-Suarez

2018-04-01

Full Text Available In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events. Cyber-attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber-attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ 1 regularization.

Building a house of sentiment on sand: Epistemological issues with contempt.

Science.gov (United States)

Lench, Heather C; Bench, Shane W; Perez, Kenneth A

2017-01-01

Contempt shares its features with other emotions, indicating that there is no justification for creating "sentiment" as a new category of feelings. Scientific categories must be created or updated on the basis of evidence. Building a new category on the currently limited contempt literature would be akin to building a house on sand - likely to fall at any moment.

Predicting Equity Markets with Digital Online Media Sentiment: Evidence from Markov-switching Models

NARCIS (Netherlands)

Nooijen, S.J.; Broda, S.A.

2016-01-01

The authors examine the predictive capabilities of online investor sentiment for the returns and volatility of MSCI U.S. Equity Sector Indices by including exogenous variables in the mean and volatility specifications of a Markov-switching model. As predicted by the semistrong efficient market

A LITERATURE SURVEY ON RECOMMENDATION SYSTEM BASED ON SENTIMENTAL ANALYSIS

OpenAIRE

Achin Jain; Vanita Jain; Nidhi Kapoor

2016-01-01

Recommender systems have grown to be a critical research subject after the emergence of the first paper on collaborative filtering in the Nineties. Despite the fact that educational studies on recommender systems, has extended extensively over the last 10 years, there are deficiencies in the complete literature evaluation and classification of that research. Because of this, we reviewed articles on recommender structures, and then classified those based on sentiment analysis. The articles are...

Short text sentiment classification based on feature extension and ensemble classifier

Science.gov (United States)

Liu, Yang; Zhu, Xie

2018-05-01

With the rapid development of Internet social media, excavating the emotional tendencies of the short text information from the Internet, the acquisition of useful information has attracted the attention of researchers. At present, the commonly used can be attributed to the rule-based classification and statistical machine learning classification methods. Although micro-blog sentiment analysis has made good progress, there still exist some shortcomings such as not highly accurate enough and strong dependence from sentiment classification effect. Aiming at the characteristics of Chinese short texts, such as less information, sparse features, and diverse expressions, this paper considers expanding the original text by mining related semantic information from the reviews, forwarding and other related information. First, this paper uses Word2vec to compute word similarity to extend the feature words. And then uses an ensemble classifier composed of SVM, KNN and HMM to analyze the emotion of the short text of micro-blog. The experimental results show that the proposed method can make good use of the comment forwarding information to extend the original features. Compared with the traditional method, the accuracy, recall and F1 value obtained by this method have been improved.

Experimental Research in Operation Management in Engine Room by using Language Sentiment/Opinion Analysis

Directory of Open Access Journals (Sweden)

Dimitris Papachristos

2014-12-01

Full Text Available The paper argues for the necessity of a combination MMR methods (questionnaire, interview and sentiment/opinion techniques to personal satisfaction analysis at the maritime and training education and proposes a generic, but practical research approach for this purpose. The proposed approach concerns the personal satisfaction evaluation of Engine Room simulator systems and combines the speech recording (sentiment/opinion analysis for measuring emotional user responses with usability testing (SUS tool. The experimental procedure presented here is a primary effort to research the emotion analysis (satisfaction of the users-students in Engine Room Simulators. Finally, the ultimate goal of this research is to find and test the critical factors that influence the educational practice and user’s satisfaction of Engine Room Simulator Systems and the ability to conduct full-time system control by the marine crew.

Applying big data technologies in the financial sector – using sentiment analysis to identify correlations in the stock market

Directory of Open Access Journals (Sweden)

Eszter Katalin Bognár

2016-06-01

Full Text Available The aim of this article is to introduce a system that is capable of collecting and analyzing different types of financial data to support traders in their decision - making. Oracle’s Big Data platform Oracle Advanced Analytics was utilized, which extends the Oracle Database with Oracle R, thus providing the opportunity to run embedded R scripts on the database server to speed up data processing. The extract, transform and load (ETL process was combined with a dictionary - based sentiment analysis module to examine cross - correlation and causality between numerical and textual financial data for a 10 week period. A notable correlation (0.42 was found between daily news sentiment scores and daily stock returns. By applying cross - correlation analysis and Granger causality testing, the results show that the news’ impact is incorporated into stock prices rapidly, having the highest correlation on the first day, while the returns’ impact on market sentiment is seen only after a few days.

Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

DEFF Research Database (Denmark)

Felbo, Bjarke; Mislove, Alan; Søgaard, Anders

2017-01-01

NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment analysis and related tasks, researchers have therefore used binarized emoticons and specific hashtags as forms of distant supervision. Our paper shows that by extending the distant supervision to a more...... diverse set of noisy labels, the models can learn richer representations. Through emoji prediction on a dataset of 1246 million tweets containing one of 64 common emojis we obtain state-of-theart performance on 8 benchmark datasets within emotion, sentiment and sarcasm detection using a single pretrained...... model. Our analyses confirm that the diversity of our emotional labels yield a performance improvement over previous distant supervision approaches....

Knowing the Other/Other Ways of Knowing: Indigenous Feminism, Testimonial, and Anti-Globalization Street Discourse

Science.gov (United States)

Dulfano, Isabel

2017-01-01

In this article, I explore the relationship between anti-globalization counter hegemonic discourse and Indigenous feminist alternative knowledge production. Although seemingly unrelated, the autoethnographic writing of some Indigenous feminists from Latin America questions the assumptions and presuppositions of Western development models and…

How do we talk about doctors and drugs? Sentiment analysis in forums expressing opinions for medical domain.

Science.gov (United States)

Jiménez-Zafra, Salud María; Martín-Valdivia, M Teresa; Molina-González, M Dolores; Ureña-López, L Alfonso

2018-04-20

The main goal of this study is to examine how people express their opinion in medical forums. We analyze the language used in order to determine the best way to tackle sentiment analysis in this domain. We have applied supervised learning and lexicon-based sentiment analysis approaches over two different corpora extracted from social web. Specifically, we have focused on two aspects: drugs and doctors. We have selected two forums and we have collected corpora for each one: (i) DOS, a Spanish corpus of drug reviews and (ii) COPOS, a Spanish corpus of patients' opinions about physicians. The classification results show that drug reviews are more difficult to classify than those about physicians. In order to understand the difference in the results, we have studied the linguistic features of both corpora. Although opinions about physicians and drugs are written in most cases by non-professional users, reviews about physicians are characterized by the use of an informal language while reviews about drugs are characterized by a combination of informal language with specific terminology (e.g. adverse effects, drug names) with greater lexical diversity, making the task of sentiment analysis difficult. Copyright © 2018 Elsevier B.V. All rights reserved.

Sentiment classification of Roman-Urdu opinions using Naïve Bayesian, Decision Tree and KNN classification techniques

Directory of Open Access Journals (Sweden)

Muhammad Bilal

2016-07-01

Full Text Available Sentiment mining is a field of text mining to determine the attitude of people about a particular product, topic, politician in newsgroup posts, review sites, comments on facebook posts twitter, etc. There are many issues involved in opinion mining. One important issue is that opinions could be in different languages (English, Urdu, Arabic, etc.. To tackle each language according to its orientation is a challenging task. Most of the research work in sentiment mining has been done in English language. Currently, limited research is being carried out on sentiment classification of other languages like Arabic, Italian, Urdu and Hindi. In this paper, three classification models are used for text classification using Waikato Environment for Knowledge Analysis (WEKA. Opinions written in Roman-Urdu and English are extracted from a blog. These extracted opinions are documented in text files to prepare a training dataset containing 150 positive and 150 negative opinions, as labeled examples. Testing data set is supplied to three different models and the results in each case are analyzed. The results show that Naïve Bayesian outperformed Decision Tree and KNN in terms of more accuracy, precision, recall and F-measure.

Machine News and Volatility: The Dow Jones Industrial Average and the TRNA Sentiment Series

NARCIS (Netherlands)

D.E. Allen (David); A.K. Singh (Abhay)

2014-01-01

markdownabstract__Abstract__ This paper features an analysis of the relationship between the volatility of the Dow Jones Industrial Average (DJIA) Index and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA) provided by SIRCA (The Securities Industry

Crusade and mission. The Islamophobia of French Catholic Anti-Semites during the nineteenth century

Directory of Open Access Journals (Sweden)

Fernando BRAVO LÓPEZ

2017-06-01

Full Text Available In this article we analyse how French Catholic Anti-Semites perceived Islam during the nineteenth century, to which end we examine the works Louis de Bonald, Louis Veuillot, Roger Gougenot des Mousseaux and D. Kimon devoted to Islam. The aim of this exercise is, firstly, to improve our knowledge of the European image of Islam in the nineteenth century, focusing on a ideological trend that has hitherto aroused scant interest among scholars. Secondly, this article will enhance our understanding of anti-Semitism as an ideology and a political movement, showing how Catholic anti-Semites, far from being solely obsessed with the Jewish peril, were also obsessed with other threats, primarily the Islamic menace. Finally, it attempts to demonstrate that, despite the arguments brandished by many scholars in recent years, anti-Islamic or Islamophobic sentiments are not necessarily based in racial prejudices, but can spring exclusively from religious intolerance. This certainly was the case among nineteenth-century French Catholic anti-Semites. However, their hostility was no less virulent because of that, far from it.

Sowing the seeds of skepticism: Russian state news and anti-GMO sentiment.

Science.gov (United States)

Dorius, Shawn F; Lawrence-Dill, Carolyn J

2018-03-21

Biotech news coverage in English-language Russian media fits the profile of the Russian information warfare strategy described in recent military reports. This raises the question of whether Russia views the dissemination of anti-GMO information as just one of many divisive issues it can exploit as part of its information war, or if GMOs serve more expansive disruptive purposes. Distinctive patterns in Russian news provide evidence of a coordinated information campaign that could turn public opinion against genetic engineering. The recent branding of Russian agriculture as the ecologically clean alternative to genetically engineered foods is suggestive of an economic motive behind the information campaign against western biotechnologies.

Integrating Piano Keyboarding into the Elementary Classroom: Effects on Memory Skills and Sentiment Toward School.

Science.gov (United States)

Marcinkiewicz, Henryk R.; And Others

1995-01-01

Discovered that the introduction of piano keyboarding into elementary school music instruction produced a positive effect regarding children's sentiment towards school. No discernible effect was revealed concerning memory skills. Includes statistical data and description of survey questionnaires. (MJP)

Using Machine Learning for Sentiment and Social Influence Analysis in Text

OpenAIRE

Kolog, Emmanuel Awuni; Montero, Calkin Suero; Toivonen, Tapani

2017-01-01

Students’ academic achievement is largely driven by their social phenomena, which is shaped by social influence and opinion dynamics. In this paper, we employed a machine learning technique to detect social influence and sentiment in text-based students’ life stories. The life stories were first pre-processed and clustered using k-means with euclidean distance. After that, we identified domestic, peer and school staff as the main influences on students’ academic development. The various influ...

Latent Dirichlet Allocation (LDA) for Sentiment Analysis Toward Tourism Review in Indonesia

Science.gov (United States)

Putri, IR; Kusumaningrum, R.

2017-01-01

The tourism industry is one of foreign exchange sector, which has considerable potential development in Indonesia. Compared to other Southeast Asia countries such as Malaysia with 18 million tourists and Singapore 20 million tourists, Indonesia which is the largest Southeast Asia’s country have failed to attract higher tourist numbers compared to its regional peers. Indonesia only managed to attract 8,8 million foreign tourists in 2013, with the value of foreign tourists each year which is likely to decrease. Apart from the infrastructure problems, marketing and managing also form of obstacles for tourism growth. An evaluation and self-analysis should be done by the stakeholder to respond toward this problem and capture opportunities that related to tourism satisfaction from tourists review. Recently, one of technology to answer this problem only relying on the subjective of statistical data which collected by voting or grading from user randomly. So the result is still not to be accountable. Thus, we proposed sentiment analysis with probabilistic topic model using Latent Dirichlet Allocation (LDA) method to be applied for reading general tendency from tourist review into certain topics that can be classified toward positive and negative sentiment.

Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

Science.gov (United States)

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti

Globalization and Dual Modes of Higher Education Policymaking in France: Je T'aime Moi Non Plus. Research & Occasional Paper Series: CSHE.2.11

Science.gov (United States)

Hoareau, Cecile

2011-01-01

The French Government has had a paradoxical relationship with globalization. Globalization is perceived as both a threat to react against and a cradle for new policy ideas. French policymakers have a love-hate relationship with the European higher education reforms that started in the 1990s, a mixed sentiment that French singer Serge Gainsbourg…

La propagande anti-britannique en France pendant l’Occupation Anti-British Propaganda in France during the Occupation

Directory of Open Access Journals (Sweden)

Françoise Passera

2009-06-01

Full Text Available Left to fight alone after France signed the armistice on the 22nd of June 1940, Great Britain became enemy number one in the eyes of the German occupying forces and the Vichy government. This hostility found expression in a considerable quantity of propaganda in the guise of posters, tracts, booklets and brochures meant to denounce British responsibility for the conflict in the eyes of French public opinion. Propaganda was particularly intense from June to December 1940 and from January to June 1944 but the German and French propaganda services waged this psychological warfare against Great Britain throughout the war. In 1940, the anti-British brainwashing campaigns aimed at ridding the defeated French of their guilt by accusing the ex-ally of being the cause of the conflict and of deceit during the Battle of France. In 1941-1942, the Allies’ military setbacks were the subject of tracts and brochures that ridiculed British strategic skills. Propaganda was also based on the painful history of France and Great Britain so as to convince the French that England had always tried to deprive France of her colonies and that it was what she was trying to do by maintaining her presence in Africa. The major part of this propaganda was promoted by the German authorities, only to a lesser degree by the French collaboration parties. Till 1942, the Information Secretariat of the Vichy government distributed few anti-British tracts, concentrating its efforts on the promotion of the National Revolution. On the other hand, the first Anglo-American bombings in the Paris area provoked strong reactions in the Vichy government which then relied on the French population’s confusion and anxiety to denounce British policy. What was the impact of these anti-British speeches on the French population? The prefects’ reports on public opinion show that the plugging of Anglophobic sentiment had little influence on the French who were globally in complete support of the

Mercurious Oil Index (MOI) : A new indicator for the global oil price

OpenAIRE

Leeuw, de, J.; Dorsman, A.B.; Nelissen, R.

2008-01-01

“The” price of oil does not exist. This paper describes the development of a (new) oil index, the Mercurious Oil Index (MOI). This index can be seen as an indicator for the global price of oil. We will discuss why this index is a reliable global price reference, and why it is superior to and more useful than the existing indices and/or benchmarks. Indices are very helpful instruments for the tracking and prediction of markets, to measure performance or sentiment and to form a solid basis on w...

Predicting online product sales via online reviews, sentiments, and promotion strategies

OpenAIRE

Chong, Alain Yee Loong; Li, Boying; Ngai, Eric W.T.; Ch'ng, Eugene; Lee, Filbert

2016-01-01

Purpose\\ud – The purpose of this paper is to investigate if online reviews (e.g. valence and volume), online promotional strategies (e.g. free delivery and discounts) and sentiments from user reviews can help predict product sales.\\ud \\ud Design/methodology/approach\\ud – The authors designed a big data architecture and deployed Node.js agents for scraping the Amazon.com pages using asynchronous input/output calls. The completed web crawling and scraping data sets were then preprocessed for se...

WikiSent : Weakly Supervised Sentiment Analysis Through Extractive Summarization With Wikipedia

OpenAIRE

Mukherjee, Subhabrata; Bhattacharyya, Pushpak

2012-01-01

This paper describes a weakly supervised system for sentiment analysis in the movie review domain. The objective is to classify a movie review into a polarity class, positive or negative, based on those sentences bearing opinion on the movie alone. The irrelevant text, not directly related to the reviewer opinion on the movie, is left out of analysis. Wikipedia incorporates the world knowledge of movie-specific features in the system which is used to obtain an extractive summary of the review...

The Potential of General Classroom Observation: Turkish EFL Teachers' Perceptions, Sentiments, and Readiness for Action

Science.gov (United States)

Merç, Ali

2015-01-01

The purpose of this study was to determine Turkish EFL teachers' attitudes towards classroom observation. 204 teachers from different school settings responded to an online questionnaire. Data were analyzed according to three types of attitudes towards classroom observation: perceptions, sentiments, and readiness for action. The findings revealed…

Reducing anti-fat prejudice in preservice health students: a randomized trial.

Science.gov (United States)

O'Brien, Kerry S; Puhl, Rebecca M; Latner, Janet D; Mir, Azeem S; Hunter, John A

2010-11-01

Anti-fat sentiment is increasing, is prevalent in health professionals, and has health and social consequences. There is no evidence for effective obesity prejudice reduction techniques in health professionals. The present experiment sought to reduce implicit and explicit anti-fat prejudice in preservice health students. Health promotion/public health bachelor degree program students (n = 159) were randomized to one of three tutorial conditions. One condition presented an obesity curriculum on the controllable reasons for obesity (i.e., diet/exercise). A prejudice reduction condition presented evidence on the uncontrollable reasons for obesity (i.e., genes/environment); whereas a neutral (control) curriculum focused on alcohol use in young people. Measures of implicit and explicit anti-fat prejudice, beliefs about obese people, and dieting, were taken at baseline and postintervention. Repeated measures analyses showed decreases in two forms of implicit anti-fat prejudice (decreases of 27 and 12%) in the genes/environment condition relative to other conditions. The diet/exercise condition showed a 27% increase in one measure of implicit anti-fat prejudice. Reductions in explicit anti-fat prejudice were also seen in the genes/environment condition (P = 0.006). No significant changes in beliefs about obese people or dieting control beliefs were found across conditions. The present results show that anti-fat prejudice can be reduced or exacerbated depending on the causal information provided about obesity. The present results have implications for the training of health professionals, especially given their widespread negativity toward overweight and obesity.

LE SENTIMENT, L’INVISIBLE DE LA PEINTURE À L’ÉPREUVE DU VISIBLE : LE COLORISME DE DELACROIX À TRAVERS LA CRITIQUE D’ART DE BAUDELAIRE (The sentiment, the invisible of the painting in the proof of the visible: the colourism of Delacroix through the art criticism of Baudelaire)

OpenAIRE

Katalin Bartha-Kovács

2015-01-01

The article aims to analyse, following the example of some paintings of Delacroix, how the “invisible part” of the painting (the sentiment, or feeling) can be made visible by the colour. To do this, we shall draw on the critical writings that Baudelaire devoted to the painting of Delacroix. At the same time, by focusing on the notion of sentiment, we shall try to connect, from a historical perspective, the colourist conception of the painting to the artistic theories of the Enlightenment, and...

The effects of pre-processing strategies in sentiment analysis of online movie reviews

Science.gov (United States)

Zin, Harnani Mat; Mustapha, Norwati; Murad, Masrah Azrifah Azmi; Sharef, Nurfadhlina Mohd

2017-10-01

With the ever increasing of internet applications and social networking sites, people nowadays can easily express their feelings towards any products and services. These online reviews act as an important source for further analysis and improved decision making. These reviews are mostly unstructured by nature and thus, need processing like sentiment analysis and classification to provide a meaningful information for future uses. In text analysis tasks, the appropriate selection of words/features will have a huge impact on the effectiveness of the classifier. Thus, this paper explores the effect of the pre-processing strategies in the sentiment analysis of online movie reviews. In this paper, supervised machine learning method was used to classify the reviews. The support vector machine (SVM) with linear and non-linear kernel has been considered as classifier for the classification of the reviews. The performance of the classifier is critically examined based on the results of precision, recall, f-measure, and accuracy. Two different features representations were used which are term frequency and term frequency-inverse document frequency. Results show that the pre-processing strategies give a significant impact on the classification process.

Who Punishes? Personality Traits Predict Individual Variation in Punitive Sentiment

Directory of Open Access Journals (Sweden)

S. Craig Roberts

2013-01-01

Full Text Available Cross-culturally, participants in public goods games reward participants and punish defectors to a degree beyond that warranted by rational, profit-maximizing considerations. Costly punishment, where individuals impose costs on defectors at a cost to themselves, is thought to promote the maintenance of cooperation. However, despite substantial variation in the extent to which people punish, little is known about why some individuals, and not others, choose to pay these costs. Here, we test whether personality traits might contribute to variation in helping and punishment behavior. We first replicate a previous study using public goods scenarios to investigate effects of sex, relatedness and likelihood of future interaction on willingness to help a group member or to punish a transgressor. As in the previous study, we find that individuals are more willing to help related than unrelated needy others and that women are more likely to express desire to help than men. Desire to help was higher if the probability of future interaction is high, at least among women. In contrast, among these variables, only participant sex predicted some measures of punitive sentiment. Extending the replication, we found that punitive sentiment, but not willingness to help, was predicted by personality traits. Most notably, participants scoring lower on Agreeableness expressed more anger towards and greater desire to punish a transgressor, and were more willing to engage in costly punishment, at least in our scenario. Our results suggest that some personality traits may contribute to underpinning individual variation in social enforcement of cooperation.

Usability/Sentiment for the Enterprise and ENTERPRISE

Science.gov (United States)

Meza, David; Berndt, Sarah

2014-01-01

The purpose of the Sentiment of Search Study for NASA Johnson Space Center (JSC) is to gain insight into the intranet search environment. With an initial usability survey, the authors were able to determine a usability score based on the Systems Usability Scale (SUS). Created in 1986, the freely available, well cited, SUS is commonly used to determine user perceptions of a system (in this case the intranet search environment). As with any improvement initiative, one must first examine and document the current reality of the situation. In this scenario, a method was needed to determine the usability of a search interface in addition to the user's perception on how well the search system was providing results. The use of the SUS provided a mechanism to quickly ascertain information in both areas, by adding one additional open-ended question at the end. The first ten questions allowed us to examine the usability of the system, while the last questions informed us on how the users rated the performance of the search results. The final analysis provides us with a better understanding of the current situation and areas to focus on for improvement. The power of search applications to enhance knowledge transfer is indisputable. The performance impact for any user unable to find needed information undermines project lifecycle, resource and scheduling requirements. Ever-increasing complexity of content and the user interface make usability considerations for the intranet, especially for search, a necessity instead of a 'nice-to-have'. Despite these arguments, intranet usability is largely disregarded due to lack of attention beyond the functionality of the infrastructure (White, 2013). The data collected from users of the JSC search system revealed their overall sentiment by means of the widely-known System Usability Scale. Results of the scores suggest 75%, +/-0.04, of the population rank the search system below average. In terms of a grading scaled, this equated to D or

The Relationship Between SERVQUAL, National Customer Satisfaction Indices, and Consumer Sentiment

DEFF Research Database (Denmark)

Kristensen, Kai; Eskildsen, Jacob Kjær

2012-01-01

The focus of this study is to integrate SERVQUAL with a national customer satisfaction index, in this context, the Extended Performance Satisfaction Index Rating framework (EPSI Rating), the European counterpart to the American Customer Satisfaction Index, and to explore the possible relationship...... with consumer sentiment measures. The data for this study come from the Danish Customer Satisfaction Index 2007. Here approximately 1700 customers evaluated their preferred bank. The questionnaire consists of two parts: the basic EPSI statement, as well as 15 statements covering the five dimensions from...

Investigating the Emotional Responses of Individuals to Urban Green Space Using Twitter Data: A Critical Comparison of Three Different Methods of Sentiment Analysis

Directory of Open Access Journals (Sweden)

Helen Roberts

2018-03-01

Full Text Available In urban research, Twitter data have the potential to provide additional information about urban citizens, their activities, mobility patterns and emotion. Extracting the sentiment present in tweets is increasingly recognised as a valuable approach to gathering information on the mood, opinion and emotional responses of individuals in a variety of contexts. This article evaluates the potential of deriving emotional responses of individuals while they experience and interact with urban green space. A corpus of over 10,000 tweets relating to 60 urban green spaces in Birmingham, United Kingdom was analysed for positivity, negativity and specific emotions, using manual, semi-automated and automated methods of sentiment analysis and the outputs of each method compared. Similar numbers of tweets were annotated as positive/neutral/negative by all three methods; however, inter-method consistency in tweet assignment between the methods was low. A comparison of all three methods on the same corpus of tweets, using character emojis as an additional quality control, identifies a number of limitations associated with each approach. The results presented have implications for urban planners in terms of the choices available to identify and analyse the sentiment present in tweets, and the importance of choosing the most appropriate method. Future attempts to develop more reliable and accurate algorithms of sentiment analysis are needed and should focus on semi-automated methods.

Sentiment analysis: a comparison of deep learning neural network algorithm with SVM and naϊve Bayes for Indonesian text

Science.gov (United States)

Calvin Frans Mariel, Wahyu; Mariyah, Siti; Pramana, Setia

2018-03-01

Deep learning is a new era of machine learning techniques that essentially imitate the structure and function of the human brain. It is a development of deeper Artificial Neural Network (ANN) that uses more than one hidden layer. Deep Learning Neural Network has a great ability on recognizing patterns from various data types such as picture, audio, text, and many more. In this paper, the authors tries to measure that algorithm’s ability by applying it into the text classification. The classification task herein is done by considering the content of sentiment in a text which is also called as sentiment analysis. By using several combinations of text preprocessing and feature extraction techniques, we aim to compare the precise modelling results of Deep Learning Neural Network with the other two commonly used algorithms, the Naϊve Bayes and Support Vector Machine (SVM). This algorithm comparison uses Indonesian text data with balanced and unbalanced sentiment composition. Based on the experimental simulation, Deep Learning Neural Network clearly outperforms the Naϊve Bayes and SVM and offers a better F-1 Score while for the best feature extraction technique which improves that modelling result is Bigram.

Using Social Media Sentiment Analysis to Understand Audiences

DEFF Research Database (Denmark)

McGuire, Mark; Kampf, Constance Elizabeth

2015-01-01

approach for contextually understanding social media posts. The human interaction step in ad-hoc corpus analysis is central to this methodology as it provides a means to ask critical questions of the content curated through the ad-hoc corpus directly. Results of ad-hoc corpus analysis from this critical......Social media communication is changing the opportunities for technical communicators to really understand audiences when these audiences are active about issues on social media platforms. Through applying ad-hoc corpus building processes to create word lists relevant to specific organizational...... projects, technical communicators can listen to their external users and identify areas of importance with greater accuracy. While other methods of sentiment analysis look for a solution that leads to artificial intelligence in the program, this paper identifies the present needs of a human interaction...

Agricultural Water Use under Global Change

Science.gov (United States)

Zhu, T.; Ringler, C.; Rosegrant, M. W.

2008-12-01

Irrigation is by far the single largest user of water in the world and is projected to remain so in the foreseeable future. Globally, irrigated agricultural land comprises less than twenty percent of total cropland but produces about forty percent of the world's food. Increasing world population will require more food and this will lead to more irrigation in many areas. As demands increase and water becomes an increasingly scarce resource, agriculture's competition for water with other economic sectors will be intensified. This water picture is expected to become even more complex as climate change will impose substantial impacts on water availability and demand, in particular for agriculture. To better understand future water demand and supply under global change, including changes in demographic, economic and technological dimensions, the water simulation module of IMPACT, a global water and food projection model developed at the International Food Policy Research Institute, is used to analyze future water demand and supply in agricultural and several non-agricultural sectors using downscaled GCM scenarios, based on water availability simulation done with a recently developed semi-distributed global hydrological model. Risk analysis is conducted to identify countries and regions where future water supply reliability for irrigation is low, and food security may be threatened in the presence of climate change. Gridded shadow values of irrigation water are derived for global cropland based on an optimization framework, and they are used to illustrate potential irrigation development by incorporating gridded water availability and existing global map of irrigation areas.

Relative Deprivation and Relative Wealth Enhances Anti-Immigrant Sentiments: The V-Curve Re-Examined.

Directory of Open Access Journals (Sweden)

Jolanda Jetten

Full Text Available Previous research has shown that negative attitudes towards immigrants and support for anti-immigrant parties are observed both among those experiencing relative deprivation and those experiencing relative gratification (so called v-curve. Whereas the effect of relative deprivation is intuitive, the effect of relative gratification is more difficult to explain. Why would economic prosperity provoke negative attitudes towards immigrants? We first present correlational (Study 1 and experimental (Study 2 support for the v-curve. In Study 1, in a national Swiss referendum, a higher percentage anti-immigrant voting was found in cantons with relatively lower and relatively higher relative disposable income. In Study 2, in a hypothetical society, more opposition to 'newcomers' joining society was found among poor or above average wealth group members than among those in a moderate wealth group condition. In Study 3, we replicate this finding and also show that opposition to immigration is higher for all wealth groups when societal inequality is growing rather than declining. In a final study, we examine different forms of relative gratification and mediators of the relationship between relative gratification and opposition to immigration (i.e., identification, collective self-definition as competent and cold, and fear about future wealth. Only fear about future wealth mediates this relationship. We conclude that, paradoxically, relative gratification effects are partly due to the fear of future deprivation.

Mechanisms of action underlying the anti-inflammatory and immunomodulatory effects of propolis: a brief review

Directory of Open Access Journals (Sweden)

Marcio A. R. Araujo

2011-09-01

Full Text Available Many biological properties have been attributed to various types of propolis, including anti-inflammatory, antimicrobial, antioxidant, antitumor, wound healing, and immunomodulatory activities. This article reviewed studies published that investigated the anti-inflammatory activity of propolis of different origins and/or its isolated components, focusing on the mechanisms of action underlying this activity and also addressing some aspects of immunomodulatory effects. The search was performed of the following databases: PubMed, Science Direct, HighWire Press, Scielo, Google Academics, Research Gate and ISI Web of Knowledgement. The anti-inflammatory activity was associated with propolis or compounds such as polyphenols (flavonoids, phenolic acids and their esters, terpenoids, steroids and amino acids. CAPE is the most studied compounds. The main mechanisms underlying the anti-inflammatory activity of propolis included the inhibition of cyclooxygenase and consequent inhibition of prostaglandin biosynthesis, free radical scavenging, inhibition of nitric oxide synthesis, reduction in the concentration of inflammatory cytokines and immunosuppressive activity. Propolis was found to exert an anti-inflammatory activity in vivo and in vitro models of acute and chronic inflammation and others studies, indicating its promising potential as anti-inflammatory agent of natural origin and as a source of chemical compounds for the development of new drugs.

A. Bandura. Auto-efficacité. Le sentiment d’efficacité personnelle

OpenAIRE

Rondier, Maïlys

2009-01-01

Albert Bandura est docteur en psychologie et enseigne à l’université de Stanford (Californie). Il est l’auteur de L’Apprentissage social (Mardaga, 1985). Depuis les années 80, Albert Bandura s’intéresse au sentiment d’efficacité personnelle. Ce concept s’inscrit dans le cadre de la théorie sociocognitive (théorie issue du béhaviorisme et du cognitivisme). Selon cette théorie, le fonctionnement et le développement psychologique doivent être compris en considérant trois facteurs en interaction ...

How does ocean ventilation change under global warming?

Directory of Open Access Journals (Sweden)

A. Gnanadesikan

2007-01-01

Full Text Available Since the upper ocean takes up much of the heat added to the earth system by anthropogenic global warming, one would expect that global warming would lead to an increase in stratification and a decrease in the ventilation of the ocean interior. However, multiple simulations in global coupled climate models using an ideal age tracer which is set to zero in the mixed layer and ages at 1 yr/yr outside this layer show that the intermediate depths in the low latitudes, Northwest Atlantic, and parts of the Arctic Ocean become younger under global warming. This paper reconciles these apparently contradictory trends, showing that the decreases result from changes in the relative contributions of old deep waters and younger surface waters. Implications for the tropical oxygen minimum zones, which play a critical role in global biogeochemical cycling are considered in detail.

Policies designed for self-interested citizens may undermine "the moral sentiments": evidence from economic experiments.

Science.gov (United States)

Bowles, Samuel

2008-06-20

High-performance organizations and economies work on the basis not only of material interests but also of Adam Smith's "moral sentiments." Well-designed laws and public policies can harness self-interest for the common good. However, incentives that appeal to self-interest may fail when they undermine the moral values that lead people to act altruistically or in other public-spirited ways. Behavioral experiments reviewed here suggest that economic incentives may be counterproductive when they signal that selfishness is an appropriate response; constitute a learning environment through which over time people come to adopt more self-interested motivations; compromise the individual's sense of self-determination and thereby degrade intrinsic motivations; or convey a message of distrust, disrespect, and unfair intent. Many of these unintended effects of incentives occur because people act not only to acquire economic goods and services but also to constitute themselves as dignified, autonomous, and moral individuals. Good organizational and institutional design can channel the material interests for the achievement of social goals while also enhancing the contribution of the moral sentiments to the same ends.

LE SENTIMENT, L’INVISIBLE DE LA PEINTURE À L’ÉPREUVE DU VISIBLE : LE COLORISME DE DELACROIX À TRAVERS LA CRITIQUE D’ART DE BAUDELAIRE (The sentiment, the invisible of the painting in the proof of the visible: the colourism of Delacroix through the art criticism of Baudelaire

Directory of Open Access Journals (Sweden)

Katalin Bartha-Kovács

2015-06-01

Full Text Available The article aims to analyse, following the example of some paintings of Delacroix, how the “invisible part” of the painting (the sentiment, or feeling can be made visible by the colour. To do this, we shall draw on the critical writings that Baudelaire devoted to the painting of Delacroix. At the same time, by focusing on the notion of sentiment, we shall try to connect, from a historical perspective, the colourist conception of the painting to the artistic theories of the Enlightenment, and point up the modifications undergone by this concept within French discourse on art.

?When ?Bad? is ?Good??: Identifying Personal Communication and Sentiment in Drug-Related Tweets

OpenAIRE

Daniulaityte, Raminta; Chen, Lu; Lamy, Francois R; Carlson, Robert G; Thirunarayan, Krishnaprasad; Sheth, Amit

2016-01-01

Background To harness the full potential of social media for epidemiological surveillance of drug abuse trends, the field needs a greater level of automation in processing and analyzing social media content. Objectives The objective of the study is to describe the development of supervised machine-learning techniques for the eDrugTrends platform to automatically classify tweets by type/source of communication (personal, official/media, retail) and sentiment (positive, negative, neutral) expre...

Detecting tweet-based sentiment polarity of plastic surgery treatment

International Nuclear Information System (INIS)

Jokhio, M.; Mahoto, N.A.

2015-01-01

Sentiment analysis is a growing research these days. Many companies perform this analysis on public opinions to get a general idea about any product or service. This paper presents a novel approach to get views or comments of Twitter users about plastic surgery treatments. The proposed approach uses machine-learning technique embedded with the naive Bayesian classifier to assign polarities (i.e. positive, negative or neutral) to the tweets, collected from Twitter micro-blogging website. The accuracy of the obtained results has been validated using precision, recall and F-score measures. It has been observed from 25000 tweets dataset that people tend to have positive as well as substantial negative opinions regarding particular treatments. The experimental results show the effectiveness of the proposed approach. (author)

Emotional Indoctrination through Sentimental Narrative in Spanish Primary Education Textbooks during the Franco Dictatorship (1939-1959)

Science.gov (United States)

Mahamud, Kira

2016-01-01

This paper aims to highlight the prominence and relevance attached by the Franco dictatorial regime to emotions and sentiments in primary education textbooks. The authors of school textbooks employed a singular writing style, which enabled them to permeate the regime's ideology within the primary education community and classroom. Overcoming the…

Le temps du paysage. Alexandre de Humboldt et la géohistoire du sentiment de la nature

OpenAIRE

Briffaud , Serge

2006-01-01

L'article propose une analyse de la théorie de Humboldt, exposé notamment dans Cosmos, sur l'histoire du sentiment de la nature et les étapes de l'émergence d'une vision "paysagère" de la nature en Occident.

An entropy based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series

NARCIS (Netherlands)

D.E. Allen (David); M.J. McAleer (Michael); A.K. Singh (Abhay)

2016-01-01

textabstractThis paper features an analysis of the relationship between the DOW JONES Industrial Average Index (DJIA) and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA)1 provided by SIRCA (The Securities Industry Research Centre of the Asia Pacic).

Behavioural breaks in the heterogeneous agent model: The impact of herding, overconfidence, and market sentiment

Czech Academy of Sciences Publication Activity Database

Kukačka, Jiří; Baruník, Jozef

2013-01-01

Roč. 392, č. 23 (2013), s. 5920-5938 ISSN 0378-4371 R&D Projects: GA ČR GA402/09/0965 Institutional support: RVO:67985556 Keywords : Heterogeneous agent model * Behavioural finance * Herding * Overconfidence * Market sentiment * Stock market crash Subject RIV: AH - Economics Impact factor: 1.722, year: 2013 http://library.utia.cas.cz/separaty/2013/E/barunik-0395344.pdf

Staying Home While Studying Abroad: Anti-Imperial Praxis for Globalizing Feminist Visions

Directory of Open Access Journals (Sweden)

Shireen Roshanravan

2012-05-01

Full Text Available This paper hinges on the recognition that when study-abroad opportunities are presented and perceived as a means of access to global perspectives on women and gender, they reduce the problem of US-centrism in Women's Studies to a geographic rather than an epistemic limitation. According to this logic, physical travel away from the United States can serve as an effective method for overcoming US-centrism and attending to the "global," a curricular strategy that Chandra Mohanty and M. Jacqui Alexander call "the cartographic rule of the transnational as always 'elsewhere'" (Mohanty and Alexander 2010, 33. This cartographic rule reinforces hegemonic representations of the United States as a unified "modern" white/Anglo nation against which the culturally Other terrain of the "global" becomes understandable. As such, the study-abroad approach to internationalizing US Women's Studies relies on the re-erasure of US Women of Color genealogies and epistemologies that disrupt the white/Anglo cultural assumptions grounding the field's central category of "woman/women." If challenging US-centrism in US Women's Studies is meant to dismantle the white/Anglo monocultural perspective of US imperialism, I argue that the geographic travel imperative of "study abroad" must be tempered by a re-inhabitation of the field through the radical genealogies and epistemologies of US Women of Color, a strategy I call the anti-imperial feminist praxis of "staying home."

Detecting Tweet-Based Sentiment Polarity of Plastic Surgery Treatment

Directory of Open Access Journals (Sweden)

Marvi Jokhio

2015-10-01

Full Text Available Sentiment analysis is a growing research these days. Many companies perform this analysis on public opinions to get a general idea about any product or service. This paper presents a novel approach to get views or comments of Twitter users about plastic surgery treatments. The proposed approach uses machine-learning technique embedded with the naïve Bayesian classifier to assign polarities (i.e. positive, negative or neutral to the tweets, collected from ?Twitter micro-blogging website?. The accuracy of the obtained results has been validated using precision, recall and F-score measures. It has been observed from 25000 tweets dataset that people tend to have positive as well as substantial negative opinions regarding particular treatments. The experimental results show the effectiveness of the proposed approach

Impact of corpus domain for sentiment classification: An evaluation study using supervised machine learning techniques

Science.gov (United States)

Karsi, Redouane; Zaim, Mounia; El Alami, Jamila

2017-07-01

Thanks to the development of the internet, a large community now has the possibility to communicate and express its opinions and preferences through multiple media such as blogs, forums, social networks and e-commerce sites. Today, it becomes clearer that opinions published on the web are a very valuable source for decision-making, so a rapidly growing field of research called “sentiment analysis” is born to address the problem of automatically determining the polarity (Positive, negative, neutral,…) of textual opinions. People expressing themselves in a particular domain often use specific domain language expressions, thus, building a classifier, which performs well in different domains is a challenging problem. The purpose of this paper is to evaluate the impact of domain for sentiment classification when using machine learning techniques. In our study three popular machine learning techniques: Support Vector Machines (SVM), Naive Bayes and K nearest neighbors(KNN) were applied on datasets collected from different domains. Experimental results show that Support Vector Machines outperforms other classifiers in all domains, since it achieved at least 74.75% accuracy with a standard deviation of 4,08.

A Sentiment-Enhanced Hybrid Recommender System for Movie Recommendation: A Big Data Analytics Framework

OpenAIRE

Wang, Yibo; Wang, Mingming; Xu, Wei

2018-01-01

Movie recommendation in mobile environment is critically important for mobile users. It carries out comprehensive aggregation of user’s preferences, reviews, and emotions to help them find suitable movies conveniently. However, it requires both accuracy and timeliness. In this paper, a movie recommendation framework based on a hybrid recommendation model and sentiment analysis on Spark platform is proposed to improve the accuracy and timeliness of mobile movie recommender system. In the propo...

Projection of Heat Waves over China under Different Global Warming Targets

Science.gov (United States)

Guo, Xiaojun; Luo, Yong; Huang, Jianbin; Zhao, Zongci

2015-04-01

Global warming targets, which are determined in terms of global mean temperature increases relative to pre-industrial temperature levels, have been one of the heated issues recently. And the climate change (especially climate extremes) and its impacts under different targets have been paid extensive concerns. In this study, evaluation and projection of heat waves in China were carried out by five CMIP5 global climate models (GCMs) with a 0.5°×0.5° horizontal resolution which were derived from EU WATCH project. A new daily observed gridded dataset CN05.1 (0.5°×0.5°) was also used to evaluate the GCMs. And four indices (heat waves frequency, longest heat waves duration, heat waves days and high temperature days) were adopted to analyze the heat waves. Compared with the observations, the five GCMs and its Multi-Model Ensemble (MME) have a remarkable capacity of reproducing the spatial and temporal characteristic of heat waves. The time correlation coefficients between MME and the observation results can all reach 0.05 significant levels. Based on the projection data of five GCMs, both the median year of crossing 1.5°C, 2°C, 2.5°, 3°C, 3.5°C, 4°C, 4.5°C and 5°C global warming targets and the corresponding climate change over China were analyzed under RCP 4.5 and RCP 8.5 scenarios, respectively. The results show that when the global mean surface air temperature rise to different targets with respect to the pre-industrial times (1861-1880), the frequency and intensity of heat waves will increase dramatically. To take the high emission scenario RCP8.5 as an example, under the RCP8.5 scenario, the warming rate over China is stronger than that over the globe, the temperature rise(median year) over China projected by MME are 1.77°C(2025), 2.63°C(2039), 3.39°C(2050), 3.97°C(2060), 4.82°C(2070), 5.47°C(2079) and 6.2°C(2089) under 1.5°C, 2°C, 2.5°C, 3°C, 3.5°C, 4°C and 4.5°C global warming targets, respectively. With the increase of the global

Global occurrence of anti-infectives in contaminated surface waters: Impact of income inequality between countries.

Science.gov (United States)

Segura, Pedro A; Takada, Hideshige; Correa, José A; El Saadi, Karim; Koike, Tatsuya; Onwona-Agyeman, Siaw; Ofosu-Anim, John; Sabi, Edward Benjamin; Wasonga, Oliver V; Mghalu, Joseph M; dos Santos Junior, Antonio Manuel; Newman, Brent; Weerts, Steven; Yargeau, Viviane

2015-07-01

The presence anti-infectives in environmental waters is of interest because of their potential role in the dissemination of anti-infective resistance in bacteria and other harmful effects on non-target species such as algae and shellfish. Since no information on global trends regarding the contamination caused by these bioactive substances is yet available, we decided to investigate the impact of income inequality between countries on the occurrence of anti-infectives in surface waters. In order to perform such study, we gathered concentration values reported in the peer-reviewed literature between 1998 and 2014 and built a database. To fill the gap of knowledge on occurrence of anti-infectives in African countries, we also collected 61 surface water samples from Ghana, Kenya, Mozambique and South Africa, and measured concentrations of 19 anti-infectives. A mixed one-way analysis of covariance (ANCOVA) model, followed by Turkey-Kramer post hoc tests was used to identify potential differences in anti-infective occurrence between countries grouped by income level (high, upper-middle and lower-middle and low income) according to the classification by the World Bank. Comparison of occurrence of anti-infectives according to income level revealed that concentrations of these substances in contaminated surface waters were significantly higher in low and lower-middle income countries (p=0.0001) but not in upper-middle income countries (p=0.0515) compared to high-income countries. We explained these results as the consequence of the absence of or limited sewage treatment performed in lower income countries. Furthermore, comparison of concentrations of low cost anti-infectives (sulfonamides and trimethoprim) and the more expensive macrolides between income groups suggest that the cost of these substances may have an impact on their environmental occurrence in lower income countries. Since wastewaters are the most important source of contamination of anti-infectives and other

Drought and Carbon Cycling of Grassland Ecosystems under Global Change: A Review

Directory of Open Access Journals (Sweden)

Tianjie Lei

2016-10-01

Full Text Available In recent years, the increased intensity and duration of droughts have dramatically altered the structure and function of grassland ecosystems, which have been forced to adapt to this change in climate. Combinations of global change drivers such as elevated atmospheric CO2 concentration, warming, nitrogen (N deposition, grazing, and land-use change have influenced the impact that droughts have on grassland C cycling. This influence, to some extent, can modify the relationship between droughts and grassland carbon (C cycling in the multi-factor world. Unfortunately, prior reviews have been primarily anecdotal from the 1930s to the 2010s. We investigated the current state of the study on the interactive impacts of multiple factors under drought scenarios in grassland C cycling and provided scientific advice for dealing with droughts and managing grassland C cycling in a multi-factor world. Currently, adequate information is not available on the interaction between droughts and global change drivers, which would advance our understanding of grassland C cycling responses. It was determined that future experiments and models should specifically test how droughts regulate grassland C cycling under global changes. Previous multi-factor experiments of current and future global change conditions have studied various drought scenarios poorly, including changes in precipitation frequency and amplitude, timing, and interactions with other global change drivers. Multi-factor experiments have contributed to quantifying these potential changes and have provided important information on how water affects ecosystem processes under global change. There is an urgent need to establish a systematic framework that can assess ecosystem dynamic responses to droughts under current and future global change and human activity, with a focus on the combined effects of droughts, global change drivers, and the corresponding hierarchical responses of an ecosystem.

Visual Sentiment Analysis of RSS News Feeds Featuring the US Presidential Election in 2008

OpenAIRE

Wanner, Franz; Rohrdantz, Christian; Mansmann, Florian; Oelke, Daniela; Keim, Daniel A.

2009-01-01

The technology behind RSS feeds offers great possibilities to retrieve more news items than ever. In contrast to these technical developments, human capabilities to read all these news items have not increased likewise. To bridge this gap, this paper presents a visual analytics tool for conducting semi-automatic sentiment analysis of large news feeds. While the tool automatically retrieves and analyzes RSS feeds with respect to positive and negative opinion words, the more demanding news anal...

Sentiment Classification of Documents in Serbian: The Effects of Morphological Normalization and Word Embeddings

Directory of Open Access Journals (Sweden)

V. Batanović

2017-11-01

Full Text Available An open issue in the sentiment classification of texts written in Serbian is the effect of different forms of morphological normalization and the usefulness of leveraging large amounts of unlabeled texts. In this paper, we assess the impact of lemmatizers and stemmers for Serbian on classifiers trained and evaluated on the Serbian Movie Review Dataset. We also consider the effectiveness of using word embeddings, generated from a large unlabeled corpus, as classification features.

The Power of Social Media Analytics: Text Analytics Based on Sentiment Analysis and Word Clouds on R

Directory of Open Access Journals (Sweden)

Ahmed Imran KABIR

2018-01-01

Full Text Available Apparently, word clouds have grown as a clear and appealing illustration or visualization strategy in terms of text. Word clouds are used as a part of various settings as a way to give a diagram by cleansing text throughout those words that come up with most frequently. Generally, this is performed constantly as an unadulterated text outline. In any case, that there is a bigger capability to this basic yet intense visualization worldview in text analytics. In this work, we investigate the adequacy of word clouds for general text analysis errands and also analyze the tweets to find out the sentiment and also discuss the legal aspects of text mining. We used R software to pull twitter data which depends altogether on word cloud as a visualization technique and also with the help of positive and negative words to determine the user sentiment. We indicate how this approach can be viably used to explain text analysis tasks and assess it in a qualitative user research.

The anti-vaccination movement and resistance to allergen-immunotherapy: a guide for clinical allergists

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Behrmann Jason

2010-09-01

Full Text Available Abstract Despite over a century of clinical use and a well-documented record of efficacy and safety, a growing minority in society questions the validity of vaccination and fear that this common public health intervention is the root-cause of severe health problems. This article questions whether growing public anti-vaccine sentiments might have the potential to spill-over into other therapies distinct from vaccination, namely allergen-immunotherapy. Allergen-immunotherapy shares certain medical vernacular with vaccination (e.g., allergy shots, allergy vaccines, and thus may become "guilty by association" due to these similarities. Indeed, this article demonstrates that anti-vaccine websites have begun unduly discrediting this allergy treatment regimen. Following an explanation of the anti-vaccine movement, the article aims to provide guidance on how clinicians can respond to patient fears towards allergen-immunotherapy in the clinical setting. This guide focuses on the provision of reliable information to patients in order to dispel misconceived associations between vaccination and allergen-immunotherapy, and the discussion of the risks and benefits of both therapies in order to assist patients in making autonomous decisions about their choice of allergy treatment.

Nostalgic Sentiment And Cultural And Creative Industries In Regional Development: A Slovak Case Study

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Borseková Kamila

2015-06-01

Full Text Available In Slovakia, there are three unique, historical mining towns, Banská Bystrica, Banská Štiavnica and Kremnica, that have been successfully turned into creative cultural centres. The historical and cultural values of those towns have stood the test of time and become a magnet for a new and creative class of people looking to escape the brutality of high modernity (modern urban centres and find a source of inspiration based on historical nostalgic sentimentalism — the basis for a new creative and cultural industry for rural areas. The main objective of this paper is to analyse the cultural and creative industries of these three unique historical mining centres with an eye to replicating their knowledge in other communities in economic stress. The paper will first explore concepts relating to cultural and creative industries with an eye towards nostalgic sentimentalism that is an important antithesis to high modernity, and even post-modernity. The second part will analyse the cultural and creative industries of the three centres based on primary data collected from several research projects in this area. The final part will provide some recommendations for the facilitation of creative and cultural enterprises in regional redevelopment. It also contains policy recommendations for the self-government of the region for a more effective and rational exploitation of the existing potential hiding in plain view.

Optimization and anti-optimization of structures under uncertainty

National Research Council Canada - National Science Library

Elishakoff, Isaac; Ohsaki, Makoto

2010-01-01

.... The necessity of anti-optimization approach is first demonstrated, then the anti-optimization techniques are applied to static, dynamic and buckling problems, thus covering the broadest possible set of applications...

The global mean energy balance under cloud-free conditions

Science.gov (United States)

Wild, Martin; Hakuba, Maria; Folini, Dois; Ott, Patricia; Long, Charles

2017-04-01

A long standing problem of climate models is their overestimation of surface solar radiation not only under all-sky, but also under clear-sky conditions (Wild et al. 1995, Wild et al. 2006). This overestimation reduced over time in consecutive model generations due to the simulation of stronger atmospheric absorption. Here we analyze the clear sky fluxes of the latest climate model generation from the Coupled Model Intercomparison Project Phase 5 (CMIP5) against an expanded and updated set of direct observations from the Baseline Surface Radiation Network (BSRN). Clear sky climatologies from these sites have been composed based on the Long and Ackermann (2000) clear sky detection algorithm (Hakuba et al. 2017), and sampling issues when comparing with model simulated clear sky fluxes have been analyzed in Ott (2017). Overall, the overestimation of clear sky insolation in the CMIP5 models is now merely 1-2 Wm-2 in the multimodel mean, compared to 4 Wm-2 in CMIP3 and 6 Wm-2 in AMIPII (Wild et al. 2006). Still a considerable spread in the individual model biases is apparent, ranging from -2 Wm-2 to 10 Wm-2 when averaged over 53 globally distributed BSRN sites. This bias structure is used to infer best estimates for present day global mean clear sky insolation, following an approach developped in Wild et al. (2013, 2015, Clim. Dyn.) for all sky fluxes. Thereby the flux biases in the various models are linearly related to their respective global means. A best estimate can then be inferred from the linear regression at the intersect where the bias against the surface observations becomes zero. This way we obtain a best estimate of 247 Wm-2 for the global mean insolation at the Earth surface under cloud free conditions, and a global mean absorbed solar radiation of 214 Wm-2 in the cloud-free atmosphere, assuming a global mean surface albedo of 13.5%. Combined with a best estimate for the net influx of solar radiation at the Top of Atmosphere under cloud free conditions

Towards Aiding Decision-Making in Social Networks by Using Sentiment and Stress Combined Analysis

OpenAIRE

Guillem Aguado; Vicente Julian; Ana Garcia-Fornes

2018-01-01

The present work is a study of the detection of negative emotional states that people have using social network sites (SNSs), and the effect that this negative state has on the repercussions of posted messages. We aim to discover in which grade a user having an affective state considered negative by an Analyzer can affect other users and generate bad repercussions. Those Analyzers that we propose are a Sentiment Analyzer, a Stress Analyzer and a novel combined Analyzer. We also want to discov...

Reduced interdecadal variability of Atlantic Meridional Overturning Circulation under global warming.

Science.gov (United States)

Cheng, Jun; Liu, Zhengyu; Zhang, Shaoqing; Liu, Wei; Dong, Lina; Liu, Peng; Li, Hongli

2016-03-22

Interdecadal variability of the Atlantic Meridional Overturning Circulation (AMOC-IV) plays an important role in climate variation and has significant societal impacts. Past climate reconstruction indicates that AMOC-IV has likely undergone significant changes. Despite some previous studies, responses of AMOC-IV to global warming remain unclear, in particular regarding its amplitude and time scale. In this study, we analyze the responses of AMOC-IV under various scenarios of future global warming in multiple models and find that AMOC-IV becomes weaker and shorter with enhanced global warming. From the present climate condition to the strongest future warming scenario, on average, the major period of AMOC-IV is shortened from ∼50 y to ∼20 y, and the amplitude is reduced by ∼60%. These reductions in period and amplitude of AMOC-IV are suggested to be associated with increased oceanic stratification under global warming and, in turn, the speedup of oceanic baroclinic Rossby waves.

Reduced interdecadal variability of Atlantic Meridional Overturning Circulation under global warming

Science.gov (United States)

Cheng, Jun; Liu, Zhengyu; Zhang, Shaoqing; Liu, Wei; Dong, Lina; Liu, Peng; Li, Hongli

2016-01-01

Interdecadal variability of the Atlantic Meridional Overturning Circulation (AMOC-IV) plays an important role in climate variation and has significant societal impacts. Past climate reconstruction indicates that AMOC-IV has likely undergone significant changes. Despite some previous studies, responses of AMOC-IV to global warming remain unclear, in particular regarding its amplitude and time scale. In this study, we analyze the responses of AMOC-IV under various scenarios of future global warming in multiple models and find that AMOC-IV becomes weaker and shorter with enhanced global warming. From the present climate condition to the strongest future warming scenario, on average, the major period of AMOC-IV is shortened from ∼50 y to ∼20 y, and the amplitude is reduced by ∼60%. These reductions in period and amplitude of AMOC-IV are suggested to be associated with increased oceanic stratification under global warming and, in turn, the speedup of oceanic baroclinic Rossby waves. PMID:26951654

The Validity and Reliability Study of Turkish Version of the Sentiments, Attitudes, and Concerns about Inclusive Education Scale

Science.gov (United States)

Cansiz, Nurcan; Cansiz, Mustafa

2018-01-01

The purpose of this study is to translate and adapt the Sentiments Attitudes and Concerns about Inclusive Education Scale (SACIE) for use in the Turkish context. For this purpose, translated version of SACIE was administered to 304 and 368 preservice teachers (PTs) to perform exploratory and confirmatory factor analysis respectively. The result of…

Global hotspots of river erosion under global warming

Science.gov (United States)

Plink-Bjorklund, P.; Reichler, T.

2017-12-01

Extreme precipitation plays a significant role for river hydrology, flood hazards and landscape response. For example, the September 2013 rainstorm in the Colorado Front Range evacuated the equivalent of hundreds to thousands of years of hillslope weathering products. Although promoted by steep topography, the Colorado event is clearly linked to rainfall intensity, since most of the 1100 debris flows occurred within the highest rainfall contour. Additional evidence for a strong link between extreme precipitation and river erosion comes from the sedimentary record, and especially from that of past greenhouse climates. The existence of such a link suggests that information about global rainfall patterns can be used to define regions of increased erosion potential. However, the question arises what rainfall criteria to use and how well the method works. A related question is how ongoing climate change and the corresponding shifts in rainfall might impact the results. Here, we use atmospheric reanalysis and output from a climate model to identify regions that are particularly susceptible to landscape change in response to extreme precipitation. In order to define the regions, we combine several hydroclimatological and geomorphological criteria into a single index of erosion potential. We show that for current climate, our criteria applied to atmospheric reanalysis or to climate model data successfully localize known areas of increased erosion potential, such as the Colorado region. We then apply our criteria to climate model data for future climate to document how the location, extent, and intensity of erosion hotspots are likely to change under global warming.

Investor sentiment and stock returns: Evidence from provincial TV audience rating in China

Science.gov (United States)

Zhang, Yongjie; Zhang, Yuzhao; Shen, Dehua; Zhang, Wei

2017-01-01

In this paper, we advocate the provincial TV audience rating as the novel proxy for the provincial investor sentiment (PIS) and investigate its relation with stock returns. The empirical results firstly show that the PIS is positively related to stock returns. Secondly, we provide direct evidence on the existence of home bias in China by observing that the provincial correlation coefficient is significantly larger than the cross-provincial correlation coefficient. Finally, the PIS can explain a large proportion of provincial comovement. To sum up, all these findings support the role of the non-traditional information sources in understanding the ;anomalies; in stock market.

The Application of Machine Learning Algorithms for Text Mining based on Sentiment Analysis Approach

Directory of Open Access Journals (Sweden)

Reza Samizade

2018-06-01

Full Text Available Classification of the cyber texts and comments into two categories of positive and negative sentiment among social media users is of high importance in the research are related to text mining. In this research, we applied supervised classification methods to classify Persian texts based on sentiment in cyber space. The result of this research is in a form of a system that can decide whether a comment which is published in cyber space such as social networks is considered positive or negative. The comments that are published in Persian movie and movie review websites from 1392 to 1395 are considered as the data set for this research. A part of these data are considered as training and others are considered as testing data. Prior to implementing the algorithms, pre-processing activities such as tokenizing, removing stop words, and n-germs process were applied on the texts. Naïve Bayes, Neural Networks and support vector machine were used for text classification in this study. Out of sample tests showed that there is no evidence indicating that the accuracy of SVM approach is statistically higher than Naïve Bayes or that the accuracy of Naïve Bayes is not statistically higher than NN approach. However, the researchers can conclude that the accuracy of the classification using SVM approach is statistically higher than the accuracy of NN approach in 5% confidence level.

Estimated migration rates under scenarios of global climate change.

Science.gov (United States)

Jay R. Malcolm; Adam Markham; Ronald P. Neilson; Michael. Oaraci

2002-01-01

Greefihouse-induced warming and resulting shifts in climatic zones may exceed the migration capabilities of some species. We used fourteen combinations of General Circulation Models (GCMs) and Global Vegetation Models (GVMs) to investigate possible migration rates required under CO2 doubled climatic forcing.

Conjunction of anti-parallel and component reconnection at the dayside MP: Cluster and Double Star coordinated observation on 6 April 2004

Science.gov (United States)

Wang, J.; Pu, Z. Y.; Fu, S. Y.; Wang, X. G.; Xiao, C. J.; Dunlop, M. W.; Wei, Y.; Bogdanova, Y. V.; Zong, Q. G.; Xie, L.

2011-05-01

Previous theoretical and simulation studies have suggested that the anti-parallel and component reconnection can occur simultaneously on the dayside magnetopause. Certain observations have also been reported to support global conjunct pattern of magnetic reconnection. Here, we show direct evidence for the conjunction of anti-parallel and component MR using coordinated observations of Double Star TC-1 and Cluster under the same IMF condition on 6 April, 2004. The global MR X-line configuration constructed is in good agreement with the “S-shape” model.

Money Laundering, Corruption and Growth: An Empirical Rationale for a Global Convergence on Anti-Money Laundering Regulation

OpenAIRE

Cavalcante Veiga, Luiz Humberto; Andrade, Joaquim Pinto

2006-01-01

This paper provides empirical evidence on the impact of anti-money laundering regulations on growth and, it examines the rationale for a global adoption of these rules. The empirical results have led us to confirm a positive relation between low corruption levels and high investment and growth. We approached the impact on growth of money laundering prevention (MLP) initiatives in two ways: first, by verifying that the existence of these initiatives affects the perception of corruption. Second...

Global Changes in Drought Conditions Under Different Levels of Warming

Science.gov (United States)

Naumann, G.; Alfieri, L.; Wyser, K.; Mentaschi, L.; Betts, R. A.; Carrao, H.; Spinoni, J.; Vogt, J.; Feyen, L.

2018-04-01

Higher evaporative demands and more frequent and persistent dry spells associated with rising temperatures suggest that drought conditions could worsen in many regions of the world. In this study, we assess how drought conditions may develop across the globe for 1.5, 2, and 3°C warming compared to preindustrial temperatures. Results show that two thirds of global population will experience a progressive increase in drought conditions with warming. For drying areas, drought durations are projected to rise at rapidly increasing rates with warming, averaged globally from 2.0 month/°C below 1.5°C to 4.2 month/°C when approaching 3°C. Drought magnitudes could double for 30% of global landmass under stringent mitigation. If contemporary warming rates continue, water supply-demand deficits could become fivefold in size for most of Africa, Australia, southern Europe, southern and central states of the United States, Central America, the Caribbean, north-west China, and parts of Southern America. In approximately 20% of the global land surface, drought magnitude will halve with warming of 1.5°C and higher levels, mainly most land areas north of latitude 55°N, but also parts of South America and Eastern and South-eastern Asia. A progressive and significant increase in frequency of droughts is projected with warming in the Mediterranean basin, most of Africa, West and Southern Asia, Central America, and Oceania, where droughts are projected to happen 5 to 10 times more frequent even under ambitious mitigation targets and current 100-year events could occur every two to five years under 3°C of warming.

Sentiment analysis in twitter data using data analytic techniques for predictive modelling

Science.gov (United States)

Razia Sulthana, A.; Jaithunbi, A. K.; Sai Ramesh, L.

2018-04-01

Sentiment analysis refers to the task of natural language processing to determine whether a piece of text contains subjective information and the kind of subjective information it expresses. The subjective information represents the attitude behind the text: positive, negative or neutral. Understanding the opinions behind user-generated content automatically is of great concern. We have made data analysis with huge amount of tweets taken as big data and thereby classifying the polarity of words, sentences or entire documents. We use linear regression for modelling the relationship between a scalar dependent variable Y and one or more explanatory variables (or independent variables) denoted X. We conduct a series of experiments to test the performance of the system.

Creative Industries: Development Processes Under Contemporary Conditions of Globalization

Directory of Open Access Journals (Sweden)

Valerija Kontrimienė

2017-06-01

Full Text Available The article deals with the processes of developing creative industries under conditions of a growth in the worldwide economy and globalization, discloses the role of the sector of creative industries and shows its place in the system of the modern global economy. The paper presents a comparative analysis of theories and theoretical approaches intended for the sector of creative industries and its development as well as defines regularities and specificities characteristic of the development of creative industries. Particular attention is shifted on the growth and development of creative industries considering the current challenges of globalization and on the most important specificities of the developing sector in the context of the challenges of economic globalization. The paper examines the trends reflecting the place of the sector of creative industries in the economy of the modern world, including the tendencies indicating changes in the export of the products created in this sector. The article considers the issues of developing creative industries and reveals priorities of future research.

THE INSTITUTIONAL INVESTORS’ BEHAVIOUR UNDER THE IMPACT OF THE GLOBAL FINANCIAL CRISIS

Directory of Open Access Journals (Sweden)

PIRTEA MARILEN

2013-02-01

Full Text Available On the subject of financial globalization a lot of literature has been written, annalyzing all sorts of effects ithad. Still, the changes induced by globalization at the level of the financial markets are not always clear. The veritableflooding of capitals, constantly moving, created a continuous game of investment opportunities, of arbitrationpossibilities and funding sources, made institutional investors adopt various attitudes, the role of institutional investorsin the activation of capital markets being sustained by the financial globalization and the extension of multinationalfinancial groups, on one side, and by the increased performance of the share and bond markets, on the other side.By the present paper, we propose to underline the behaviour of the main institutional investors (mutual funds,pension funds and hedge funds under the impact of the current global financial crisis, the modifications whichintervened in asset assignment and investment relocation, showing that the instability generated in the global financialsystem had immediate effects on all the portfolios of institutional investors, regardless of their classificationcategory.Under conditions of capital flow increase, adjusted by the global financial crisis, the presented analysis andempirical proofs show a tendency of institutional investors’ asset reallocation on developed markets and thewithdrawal from the emergent ones.

Vulnerability of Hidropower Generation in Amazon's Tributaries Under Global Change Scenarios

Science.gov (United States)

Von Randow, R.; Siqueira, J. L., Jr.; Rodriguez, D. A.; Tomasella, J.; Floriano, L. E.

2014-12-01

The Brazilian energy sector is under continued expansion. The majority of energy power generation in the country is done through hydropower, which represents around 88% of the energy originated from renewable sources in the country. Still, only 10% of the high potential for production of the Amazon basin is currently availed, and this raises attention for the implantation of new hydropower plants in the region. When a hydropower plant is considered to be built, the natural characteristics of the region are taken into account, considering that the rainfall regime follows certain stationarity. However, under the possibility of global change, the expected capacity of the plants may be compromised. The objective of this study is to evaluate if the current hydropower plants of some Amazon River tributaries can maintain their functionality under global environmental change conditions. For that, based on the discharge data and hydropower information available by Brazilian National Agency of Water and Energy we will infer the energy potential of these hydropower dams for the historic period that will be compared with the energy potential for future discharge under global environmental change conditions. The future discharge will be generated by the Distributed Hydrological Model developed at the Brazilian National Institute for Space Research (MHD-INPE), driven by different climate change scenarios projected by regional and global atmospheric models, associated with land use scenarios projected by a dynamic land use model (LUCC-ME/INPE). MHD-INPE will be calibrated through observed discharges for 1970-1990 using current land use conditions, and will generate discharges for the period of 2000 to 2050. In addition, special attention will be given to the presence of secondary forest growth in the land use scenarios in order to identify the importance of considering this use in the modelling exercise, since that use is not usually considered in hydrological modelling studies.

Charles Darwin's Theory of Moral Sentiments: What Darwin's Ethics Really Owes to Adam Smith.

Science.gov (United States)

Priest, Greg

2017-01-01

When we read the Origin, we cannot help but hear echoes of the Wealth of Nations. Darwin's "economy of nature" features a "division of labour" that leads to complexity and productivity. We should not, however, analyze Darwin's ethics through this lens. Darwin did not draw his economic ideas from Smith, nor did he base his ethics on an economic foundation. Darwin's ethics rest on Smith's notion from the Theory of Moral Sentiments of an innate human faculty of sympathy. Darwin gave this faculty an evolutionary interpretation and built on this foundation an ethics far removed from what is commonly supposed.

Hemostimulating efficiency of non-steroid anti-inflammatory drugs under modified irradiation conditions

International Nuclear Information System (INIS)

Zhvoronkov, L.P.; Sklobovskaya, I.Eh.

1988-01-01

Non-steroid anti-inflammatory drugs (NSAID) were found to have hemostimulating effect in mice after irradiation. This effect was rather definite under irradiation conditions modified by dose fractioning or radioprotective chemicals. NSAID application during fractionated irradiation with midlethal integral dose leads to almost complete recovery of bone marrow hemopoiesis by the 9th day of radiation illness. NSAID usage combined with chemical radioprotectors provides effective hemopoiesis stimulation leading to survival increase in animals, irradiated with absolutely lethal doses. (author)

Marine Microalgae with Anti-Cancer Properties.

Science.gov (United States)

Martínez Andrade, Kevin A; Lauritano, Chiara; Romano, Giovanna; Ianora, Adrianna

2018-05-15

Cancer is the leading cause of death globally and finding new therapeutic agents for cancer treatment remains a major challenge in the pursuit for a cure. This paper presents an overview on microalgae with anti-cancer activities. Microalgae are eukaryotic unicellular plants that contribute up to 40% of global primary productivity. They are excellent sources of pigments, lipids, carotenoids, omega-3 fatty acids, polysaccharides, vitamins and other fine chemicals, and there is an increasing demand for their use as nutraceuticals and food supplements. Some microalgae are also reported as having anti-cancer activity. In this review, we report the microalgal species that have shown anti-cancer properties, the cancer cell lines affected by algae and the concentrations of compounds/extracts tested to induce arrest of cell growth. We also report the mediums used for growing microalgae that showed anti-cancer activity and compare the bioactivity of these microalgae with marine anticancer drugs already on the market and in phase III clinical trials. Finally, we discuss why some microalgae can be promising sources of anti-cancer compounds for future development.

Enzymology under global change: organic nitrogen turnover in alpine and sub-Arctic soils

NARCIS (Netherlands)

Weedon, J.T.; Aerts, R.; Kowalchuk, G.A.; van Bodegom, P.M.

2011-01-01

Understanding global change impacts on the globally important carbon storage in alpine, Arctic and sub-Arctic soils requires knowledge of the mechanisms underlying the balance between plant primary productivity and decomposition. Given that nitrogen availability limits both processes, understanding

Enzymology under global change: organic nitrogen turnover in alpine and sub-Arctic soils.

NARCIS (Netherlands)

Weedon, J.T.; Aerts, R.; Kowalchuk, G.A.; van Bodegom, P.M.

2011-01-01

Understanding global change impacts on the globally important carbon storage in alpine, Arctic and sub-Arctic soils requires knowledge of the mechanisms underlying the balance between plant primary productivity and decomposition. Given that nitrogen availability limits both processes, understanding

Monitoring Crohn's disease during anti-TNF-α therapy: validation of the magnetic resonance enterography global score (MEGS) against a combined clinical reference standard

International Nuclear Information System (INIS)

Prezzi, Davide; Bhatnagar, Gauraang; Makanyanga, Jesica; Halligan, Steve; Taylor, Stuart Andrew; Vega, Roser

2016-01-01

To assess the ability of magnetic resonance enterography global score (MEGS) to characterise Crohn's disease (CD) response to anti-TNF-α therapy. Thirty-six CD patients (median age 26 years, 20 males) commencing anti-TNF-α therapy with concomitant baseline MRI enterography (MRE) were identified retrospectively. Patients' clinical course was followed and correlated with subsequent MREs. Scan order was randomised and MEGS (a global activity score) was applied by two blinded radiologists. A physician's global assessment of the disease activity (remission, mild, moderate or severe) at the time of MRE was assigned. The cohort was divided into clinical responders and non-responders and MEGS compared according to activity status and treatment response. Interobserver agreement was assessed. Median MEGS decreased significantly between baseline and first follow-up in responders (28 versus 6, P < 0.001) but was unchanged in non-responders (26 versus 18, P = 0.28). The median MEGS was significantly lower in clinical remission (9) than in moderate (14) or severe (29) activity (P < 0.001). MEGS correlated significantly with clinical activity (r = 0.53; P < 0.001). Interobserver Bland-Altman limits of agreement (BA LoA) were -19.7 to 18.5. MEGS decreases significantly in clinical responders to anti-TNF-α therapy but not in non-responders, demonstrates good interobserver agreement and moderate correlation with clinical disease activity. (orig.)

Sentimento de democracia Sentiment of democracy

Directory of Open Access Journals (Sweden)

Rubem Barboza Filho

2003-01-01

Full Text Available Este artigo explora o papel que os valores, e um certo modo de vivê-los, pode ter para a consolidação da democracia no Brasil. Na primeira parte, mostra, com o auxílio de Charles Taylor, como a proposta de democracia deliberativa e procedimental de Habermas contempla as idéias de razão e interesse bem compreendidos, mas soterra a importância do ''sentimento bem compreendido'' - dos valores que a originaram historicamente. Na segunda parte, o artigo examina as grandes configurações expressivistas e não racionalistas de valores que conformaram a identidade brasileira - o barroco, o romantismo e o modernismo - e como esta tradição, e os valores que nela habitam, podem ser mobilizados para a nossa plena democratização e para a permanência dos próprios procedimentos democráticos.This article explores the role that values, and a way of experiencing them, may have to consolidate democracy in Brazil. The first part shows, with the assistance of Charles Taylor, how Habermas's procedural and deliberative democracy accounts for the ideas of reason and self-interest rightly understood, but not for the ''sentiment rightly understood'' - the values which have made it historically possible. The second part examines the great expressivist and non-rationalist configurations which have made up the Brazilian identity - Baroque, Romanticism and Modernism - and how this tradition, and the values which inhabit it, may be worked out for our full democratization and the keeping of the democratic proceduralism itself.

Environmental and radiological remediation under Canada's global partnership program 2004-11 - 59185

International Nuclear Information System (INIS)

Washer, Michael J.

2012-01-01

Following the '911' attack on the USA in 2001 the international community under Canada's G8 leadership established a $20 billion Global Partnership initiative in 2002 to collaboratively address threats to global security posed by the proliferation and potential terrorist use of Weapons and Materials of Mass Destruction (WMMD) and related materials and knowledge. This major international initiative addressed four priority areas: (1) Chemical Weapon Destruction (2) Nuclear powered submarine eliminations (3) Nuclear and radiological security; and (4) Employment for former weapon scientists. Additionally the initiative has addressed Biological Non- Proliferation. Canada's execution of all these program areas has resulted in substantial environmental benefits aside from the eradication and securing of WMMD. This paper reviews the environmental and radiological remediation achievements of the four primary Global Partnership program areas addressed under Canadian funding 2004 through 2011. (author)

Burmese Attitude toward Chinese: Portrayal of the Chinese in Contemporary Cultural and Media Works

Directory of Open Access Journals (Sweden)

Min Zin

2012-01-01

Full Text Available This paper argues that since at least the mid 1980s, there has been an observable negative attitude among the people of Burma against the Chinese. Such sentiment is not just transient public opinion, but an attitude. The author measures it by studying contemporary cultural and media works as found in legally published expressions, so as to exclude any material rejected by the regime’s censors. The causes of such sentiment are various: massive Chinese migration and purchases of real estate (especially in Upper Burma, Chinese money that is inflating the cost of everything, and cultural “intrusion.” The sentiment extends to the military, as well: the article examines a dozen memoirs of former military generals and finds that Burma’s generals do not trust the Chinese, a legacy of China’s interference in Burma’s civil war until the 1980s. The public outcry over the Myitsone dam issue, however, was the most significant expression of such sentiment since 1969, when anti-Chinese riots broke out in Burma. The relaxation of media restrictions under the new government has allowed this expression to gather steam and spread throughout the country, especially in private weekly journals that are becoming more outspoken and daring in pushing the boundaries of the state’s restrictions.

A SVM-based method for sentiment analysis in Persian language

Science.gov (United States)

Hajmohammadi, Mohammad Sadegh; Ibrahim, Roliana

2013-03-01

Persian language is the official language of Iran, Tajikistan and Afghanistan. Local online users often represent their opinions and experiences on the web with written Persian. Although the information in those reviews is valuable to potential consumers and sellers, the huge amount of web reviews make it difficult to give an unbiased evaluation to a product. In this paper, standard machine learning techniques SVM and naive Bayes are incorporated into the domain of online Persian Movie reviews to automatically classify user reviews as positive or negative and performance of these two classifiers is compared with each other in this language. The effects of feature presentations on classification performance are discussed. We find that accuracy is influenced by interaction between the classification models and the feature options. The SVM classifier achieves as well as or better accuracy than naive Bayes in Persian movie. Unigrams are proved better features than bigrams and trigrams in capturing Persian sentiment orientation.

Ethnocentrism, Religiosity, Environmental and Health Consciousness: Motivators for Anti-Consumers

Directory of Open Access Journals (Sweden)

Ramazan KAYNAK

2011-11-01

Full Text Available This paper covers highlighting the importance of anti-consumer groups in today’s markets and several outstanding factors shaping their reaction against consumption, which are ethnocentrism, religiosity, environmental and health consciousness. A conceptual model is presented which examines the explaining power of ethnocentrism, religiosity, environmental and health consciousness upon voluntary simplifiers and global impact consumers. Data were collected through an e-questionnaire by sending posts to the anti-consumer websites. A total of 503 useable responses were retained for analysis. The analysis reveals that ethnocentrism, environmental and health consciousness have significant impacts upon anti-consumers. In addition, religiosity has a negative impact upon global impact consumers’ anti-consumption behavior. Raising sensitiveness to environmental and health consciousness and ethnocentrism with regards to dealing with anti-consumers enables companies to have sustainable competitive power. These consumers’ growing satisfaction contributes to consumer loyalty in addition to an increase in market share. Researches related to anti-consumers have traditionally emphasized their impacts upon companies’ profits and reputation. On the contrary, this study reveals the main motivations behind voluntary simplifiers and global impact consumers and puts forth a new perspective by presenting the findings related to anti-consumers in Turkey.

Introduction : sentiments d’efficacité personnelle et orientation scolaire et professionnelle1

OpenAIRE

Blanchard, Serge

2011-01-01

Ce numéro spécial poursuit quatre objectifs : Présenter la théorie des sentiments d’efficacité personnelle (SEP) – qui s’insère dans le cadre plus général de la théorie sociale cognitive (TSC) d’Albert Bandura – et les principaux résultats des recherches qu’elle a suscitées depuis vingt-cinq ans aux États-Unis dans le domaine de l’orientation scolaire et professionnelle.L’article de Stephen Brewer présente d’abord une biographie d’Albert Bandura puis une brève introduction à ses travaux. Il d...

The painful tweet: text, sentiment, and community structure analyses of tweets pertaining to pain.

Science.gov (United States)

Tighe, Patrick J; Goldsmith, Ryan C; Gravenstein, Michael; Bernard, H Russell; Fillingim, Roger B

2015-04-02

Despite the widespread popularity of social media, little is known about the extent or context of pain-related posts by users of those media. The aim was to examine the type, context, and dissemination of pain-related tweets. We used content analysis of pain-related tweets from 50 cities to unobtrusively explore the meanings and patterns of communications about pain. Content was examined by location and time of day, as well as within the context of online social networks. The most common terms published in conjunction with the term "pain" included feel (n=1504), don't (n=702), and love (n=649). The proportion of tweets with positive sentiment ranged from 13% in Manila to 56% in Los Angeles, CA, with a median of 29% across cities. Temporally, the proportion of tweets with positive sentiment ranged from 24% at 1600 to 38% at 2400, with a median of 32%. The Twitter-based social networks pertaining to pain exhibited greater sparsity and lower connectedness than did those social networks pertaining to common terms such as apple, Manchester United, and Obama. The number of word clusters in proportion to node count was greater for emotion terms such as tired (0.45), happy (0.43), and sad (0.4) when compared with objective terms such as apple (0.26), Manchester United (0.14), and Obama (0.25). Taken together, our results suggest that pain-related tweets carry special characteristics reflecting unique content and their communication among tweeters. Further work will explore how geopolitical events and seasonal changes affect tweeters' perceptions of pain and how such perceptions may affect therapies for pain.

Hypothyroidism in Cancer Patients on Immune Checkpoint Inhibitors with anti-PD1 Agents: Insights on Underlying Mechanisms.

Science.gov (United States)

Alhusseini, M; Samantray, J

2017-04-01

Background: Immune therapy using monoclonal antibodies against cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death 1 receptor (PD-1) for various cancers have been reported to cause thyroid dysfunction. Little is known, however, about the underlying pathogenic mechanisms and the course of hypothyroidism that subsequently develops. In this report, we use the change in thyroglobulin and thyroid antibody levels in patients on immune therapy who develop hypothyroidism to better understand its pathogenesis as well as examine the status of hypothyroidism in the long term. Methods: We report a case series of 10 patients who developed hypothyroidism after initiation of immune therapy (either anti-PD-1 alone or in combination with anti-CTLA-4). Available thyroid antibodies including anti-thyroglobulin (anti-Tg), anti-thyroid peroxidase (anti-TPO), and thyroid stimulating immunoglobulin (TSI) were noted during the initial thyroiditis phase as well as the hypothyroid phase. Persistence or remission of hypothyroidism was noted at 6 months. Summary: During the thyroiditis phase, 50% of the patients had elevated Tg titers, 40% had elevated anti-Tg, and 40% had elevated TSI. All of these titers decreased during the hypothyroid phase. Permanent hypothyroidism was noted in 80% of the cases. Conclusion: Hypothyroidism following initiation of immune therapy has immunologic and non-immunologic mediated mechanisms and is likely to be persistent. © Georg Thieme Verlag KG Stuttgart · New York.

An implementation of support vector machine on sentiment classification of movie reviews

Science.gov (United States)

Yulietha, I. M.; Faraby, S. A.; Adiwijaya; Widyaningtyas, W. C.

2018-03-01

With technological advances, all information about movie is available on the internet. If the information is processed properly, it will get the quality of the information. This research proposes to the classify sentiments on movie review documents. This research uses Support Vector Machine (SVM) method because it can classify high dimensional data in accordance with the data used in this research in the form of text. Support Vector Machine is a popular machine learning technique for text classification because it can classify by learning from a collection of documents that have been classified previously and can provide good result. Based on number of datasets, the 90-10 composition has the best result that is 85.6%. Based on SVM kernel, kernel linear with constant 1 has the best result that is 84.9%

Prediction of Typhoon Wind Speeds under Global Warming Conditions

International Nuclear Information System (INIS)

Choun, Young Sun; Kim, Min Kyu; Kang, Ju Whan; Kim, Yang Seon

2016-01-01

The continuous increase of SST by global warming conditions in the western North Pacific Ocean results in an increased occurrence of supertyphoons in East Asia and the Korean Peninsula. Recent numerical experiments have found that the central pressures of two historical typhoons, Maemi (2003) and Rusa (2002), which recorded the highest storm surges along the coasts of the Korean Peninsula, dropped about 19 and 17 hPa, respectively, when considering the future SST (a warming of 3.9 .deg. C for 100 years) over the East China Sea. The maximum wind speeds increase under global warming conditions. The probability of occurrence of super-typhoons increases in the future. The estimated return period for supertyphoons affecting the Younggwang site is about 1,000,000 years.

Prediction of Typhoon Wind Speeds under Global Warming Conditions

Energy Technology Data Exchange (ETDEWEB)

Choun, Young Sun; Kim, Min Kyu [KAERI, Daejeon (Korea, Republic of); Kang, Ju Whan; Kim, Yang Seon [Mokpo National University, Muan (Korea, Republic of)

2016-05-15

The continuous increase of SST by global warming conditions in the western North Pacific Ocean results in an increased occurrence of supertyphoons in East Asia and the Korean Peninsula. Recent numerical experiments have found that the central pressures of two historical typhoons, Maemi (2003) and Rusa (2002), which recorded the highest storm surges along the coasts of the Korean Peninsula, dropped about 19 and 17 hPa, respectively, when considering the future SST (a warming of 3.9 .deg. C for 100 years) over the East China Sea. The maximum wind speeds increase under global warming conditions. The probability of occurrence of super-typhoons increases in the future. The estimated return period for supertyphoons affecting the Younggwang site is about 1,000,000 years.

Designing Supervision under the preventive Anti-money laundering policy in the European Union

OpenAIRE

van den Broek, Melissa

2014-01-01

Directive 2005/60/EC on the prevention of the use of the financial system for the purpose of money laundering and terrorist financing is currently one of the main instruments which regulates efforts to combat money laundering (and terrorist financing) in the European Union. Respecting national procedural autonomy, this directive leaves a high degree of freedom for the Member States in designing their own supervisory architectures under the preventive anti-money laundering policy. This contrib...

A Novel, Gradient Boosting Framework for Sentiment Analysis in Languages where NLP Resources Are Not Plentiful: A Case Study for Modern Greek

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Vasileios Athanasiou

2017-03-01

Full Text Available Sentiment analysis has played a primary role in text classification. It is an undoubted fact that some years ago, textual information was spreading in manageable rates; however, nowadays, such information has overcome even the most ambiguous expectations and constantly grows within seconds. It is therefore quite complex to cope with the vast amount of textual data particularly if we also take the incremental production speed into account. Social media, e-commerce, news articles, comments and opinions are broadcasted on a daily basis. A rational solution, in order to handle the abundance of data, would be to build automated information processing systems, for analyzing and extracting meaningful patterns from text. The present paper focuses on sentiment analysis applied in Greek texts. Thus far, there is no wide availability of natural language processing tools for Modern Greek. Hence, a thorough analysis of Greek, from the lexical to the syntactical level, is difficult to perform. This paper attempts a different approach, based on the proven capabilities of gradient boosting, a well-known technique for dealing with high-dimensional data. The main rationale is that since English has dominated the area of preprocessing tools and there are also quite reliable translation services, we could exploit them to transform Greek tokens into English, thus assuring the precision of the translation, since the translation of large texts is not always reliable and meaningful. The new feature set of English tokens is augmented with the original set of Greek, consequently producing a high dimensional dataset that poses certain difficulties for any traditional classifier. Accordingly, we apply gradient boosting machines, an ensemble algorithm that can learn with different loss functions providing the ability to work efficiently with high dimensional data. Moreover, for the task at hand, we deal with a class imbalance issues since the distribution of sentiments in

Religion and the Unmaking of Prejudice toward Muslims: Evidence from a Large National Sample

Science.gov (United States)

Shaver, John H.; Troughton, Geoffrey; Sibley, Chris G.; Bulbulia, Joseph A.

2016-01-01

In the West, anti-Muslim sentiments are widespread. It has been theorized that inter-religious tensions fuel anti-Muslim prejudice, yet previous attempts to isolate sectarian motives have been inconclusive. Factors contributing to ambiguous results are: (1) failures to assess and adjust for multi-level denomination effects; (2) inattention to demographic covariates; (3) inadequate methods for comparing anti-Muslim prejudice relative to other minority group prejudices; and (4) ad hoc theories for the mechanisms that underpin prejudice and tolerance. Here we investigate anti-Muslim prejudice using a large national sample of non-Muslim New Zealanders (N = 13,955) who responded to the 2013 New Zealand Attitudes and Values Study. We address previous shortcomings by: (1) building Bayesian multivariate, multi-level regression models with denominations modeled as random effects; (2) including high-resolution demographic information that adjusts for factors known to influence prejudice; (3) simultaneously evaluating the relative strength of anti-Muslim prejudice by comparing it to anti-Arab prejudice and anti-immigrant prejudice within the same statistical model; and (4) testing predictions derived from the Evolutionary Lag Theory of religious prejudice and tolerance. This theory predicts that in countries such as New Zealand, with historically low levels of conflict, religion will tend to increase tolerance generally, and extend to minority religious groups. Results show that anti-Muslim and anti-Arab sentiments are confounded, widespread, and substantially higher than anti-immigrant sentiments. In support of the theory, the intensity of religious commitments was associated with a general increase in tolerance toward minority groups, including a poorly tolerated religious minority group: Muslims. Results clarify religion’s power to enhance tolerance in peaceful societies that are nevertheless afflicted by prejudice. PMID:26959976

Religion and the Unmaking of Prejudice toward Muslims: Evidence from a Large National Sample.

Science.gov (United States)

Shaver, John H; Troughton, Geoffrey; Sibley, Chris G; Bulbulia, Joseph A

2016-01-01

In the West, anti-Muslim sentiments are widespread. It has been theorized that inter-religious tensions fuel anti-Muslim prejudice, yet previous attempts to isolate sectarian motives have been inconclusive. Factors contributing to ambiguous results are: (1) failures to assess and adjust for multi-level denomination effects; (2) inattention to demographic covariates; (3) inadequate methods for comparing anti-Muslim prejudice relative to other minority group prejudices; and (4) ad hoc theories for the mechanisms that underpin prejudice and tolerance. Here we investigate anti-Muslim prejudice using a large national sample of non-Muslim New Zealanders (N = 13,955) who responded to the 2013 New Zealand Attitudes and Values Study. We address previous shortcomings by: (1) building Bayesian multivariate, multi-level regression models with denominations modeled as random effects; (2) including high-resolution demographic information that adjusts for factors known to influence prejudice; (3) simultaneously evaluating the relative strength of anti-Muslim prejudice by comparing it to anti-Arab prejudice and anti-immigrant prejudice within the same statistical model; and (4) testing predictions derived from the Evolutionary Lag Theory of religious prejudice and tolerance. This theory predicts that in countries such as New Zealand, with historically low levels of conflict, religion will tend to increase tolerance generally, and extend to minority religious groups. Results show that anti-Muslim and anti-Arab sentiments are confounded, widespread, and substantially higher than anti-immigrant sentiments. In support of the theory, the intensity of religious commitments was associated with a general increase in tolerance toward minority groups, including a poorly tolerated religious minority group: Muslims. Results clarify religion's power to enhance tolerance in peaceful societies that are nevertheless afflicted by prejudice.

Immunochemical detection of food-derived polyphenols in the aorta: macrophages as a major target underlying the anti-atherosclerotic activity of polyphenols.

Science.gov (United States)

Kawai, Yoshichika

2011-01-01

It has been suggested that polyphenol-rich diets decrease the risk of cardiovascular diseases. Although studies of the bioavailability of polyphenols, particularly their absorption and metabolism, have been reported recently, the tissue and cellular distributions underlying their biological mechanisms remain unknown. It is difficult to evaluate the specific localization of tissue and/or cellular polyphenols, because the method is limited to chromatography. To overcome these difficulties, we have developed anti-polyphenol antibodies to characterize immunohistochemically the localization of polyphenols and their metabolites in vivo. Two novel monoclonal antibodies were raised against quercetin and tea catechins, which represent flavonoid-type polyphenols distributed in foods and beverages, and are expected to exhibit anti-oxidative and anti-inflammatory activities in vivo. Using these antibodies, we identified activated macrophages as a specific target of these flavonoids during the development of atherosclerotic lesions. This review describes recent findings on the molecular actions of flavonoids that underly their anti-atherosclerotic activity in vivo.

Antioxidant activity for spice oils (1) anti oxidative stability of thyme and caraway oil extracts under UV-irradiation

International Nuclear Information System (INIS)

Atef Ghazy, M.; Shaker, E.S.

2002-01-01

The anti oxidative activity for some spice essential oils have been investigated using thiocyanate method and compared with common natural antioxidant. The antioxidant activity for nine spice oils has been measured at 500 ppm after 13 days. The most potent one was the lemon grass (99.8), followed by orange peel, thyme, and caraway. The activities for these four oils were higher than that for Alpha-tocopherol (87.7%). Petitgrain, and geranium oils have marched activity but less than that for Alpha-tocopherol. No obvious has been found for citronella. fennel, and cardamon oils. The aqueous, butanoic, methanolic and hexanoic extracts for thyme and caraway oil exhibit effective anti oxidative activities under UV irradiation (254 nm) for 6 and 10 hr compared with that for alpha-tocopherol. The anti oxidative effect of thyme and caraway oil extracts were found to be strong and stable towards UV-irradiation, and equal to that for Alpha-tocopherol. Thyme's aqueous and caraway's hexanal extracts were the most potent extracts under the same conditions

L'influence d'un stage d'enseignement dans un musee de sciences naturelles sur le sentiment d'autoefficacite en sciences de futurs enseignants

Science.gov (United States)

Deblois, Annick

Cette etude qualitative multicas est ancree dans l'approche sociale-cognitive de la theorie de l'autoefficacite de Bandura (1977). Elle s'interesse a quatre stages a l'enseignement qui se sont deroules au Musee canadien de la nature a Ottawa, Canada, en 2009. L'utilisation de donnees secondaires issues du questionnaire STEBI-B traduit et modifie (Dionne et Couture, 2010) ainsi que des entrevues semi-dirigees ont permis une analyse du changement du sentiment d'autoefficacite en sciences chez les stagiaires. Les elements les plus interessants de cette recherche sont l'apprentissage vicariant et la possibilite de repetition qui favorise une meilleure connaissance de soi et une pratique reflexive. Les resultats, dans l'ensemble positifs, illustrent bien le potentiel d'un tel stage afin de rehausser le sentiment d'autoefficacite en sciences chez des stagiaires en enseignement, particulierement chez ceux qui se destinent a enseigner a l'elementaire puisque ceux-ci ont souvent une formation academique dans un domaine autre que les sciences.

The European climate under a 2 °C global warming

International Nuclear Information System (INIS)

Vautard, Robert; Stegehuis, Annemiek; Gobiet, Andreas; Mendlik, Thomas; Sobolowski, Stefan; Kjellström, Erik; Nikulin, Grigory; Watkiss, Paul; Landgren, Oskar; Teichmann, Claas; Jacob, Daniela

2014-01-01

A global warming of 2 °C relative to pre-industrial climate has been considered as a threshold which society should endeavor to remain below, in order to limit the dangerous effects of anthropogenic climate change. The possible changes in regional climate under this target level of global warming have so far not been investigated in detail. Using an ensemble of 15 regional climate simulations downscaling six transient global climate simulations, we identify the respective time periods corresponding to 2 °C global warming, describe the range of projected changes for the European climate for this level of global warming, and investigate the uncertainty across the multi-model ensemble. Robust changes in mean and extreme temperature, precipitation, winds and surface energy budgets are found based on the ensemble of simulations. The results indicate that most of Europe will experience higher warming than the global average. They also reveal strong distributional patterns across Europe, which will be important in subsequent impact assessments and adaptation responses in different countries and regions. For instance, a North–South (West–East) warming gradient is found for summer (winter) along with a general increase in heavy precipitation and summer extreme temperatures. Tying the ensemble analysis to time periods with a prescribed global temperature change rather than fixed time periods allows for the identification of more robust regional patterns of temperature changes due to removal of some of the uncertainty related to the global models’ climate sensitivity. (paper)

Future changes in global warming potentials under representative concentration pathways

Energy Technology Data Exchange (ETDEWEB)

Reisinger, Andy [New Zealand Agricultural Greenhouse Gas Research Centre, PO Box 10002, Wellington 6143 (New Zealand); Meinshausen, Malte [Earth System Analysis, Potsdam Institute for Climate Impact Research (Germany); Manning, Martin, E-mail: andy.reisinger@nzagrc.org.nz [Climate Change Research Institute, Victoria University of Wellington (New Zealand)

2011-04-15

Global warming potentials (GWPs) are the metrics currently used to compare emissions of different greenhouse gases under the United Nations Framework Convention on Climate Change. Future changes in greenhouse gas concentrations will alter GWPs because the radiative efficiencies of marginal changes in CO{sub 2}, CH{sub 4} and N{sub 2}O depend on their background concentrations, the removal of CO{sub 2} is influenced by climate-carbon cycle feedbacks, and atmospheric residence times of CH{sub 4} and N{sub 2}O also depend on ambient temperature and other environmental changes. We calculated the currently foreseeable future changes in the absolute GWP of CO{sub 2}, which acts as the denominator for the calculation of all GWPs, and specifically the GWPs of CH{sub 4} and N{sub 2}O, along four representative concentration pathways (RCPs) up to the year 2100. We find that the absolute GWP of CO{sub 2} decreases under all RCPs, although for longer time horizons this decrease is smaller than for short time horizons due to increased climate-carbon cycle feedbacks. The 100-year GWP of CH{sub 4} would increase up to 20% under the lowest RCP by 2100 but would decrease by up to 10% by mid-century under the highest RCP. The 100-year GWP of N{sub 2}O would increase by more than 30% by 2100 under the highest RCP but would vary by less than 10% under other scenarios. These changes are not negligible but are mostly smaller than the changes that would result from choosing a different time horizon for GWPs, or from choosing altogether different metrics for comparing greenhouse gas emissions, such as global temperature change potentials.

Oligarchy versus Democracy and Regulation versus Deregulation under the Globalization Effect

Directory of Open Access Journals (Sweden)

Dumitru-Alexandru BODISLAV

2012-05-01

Full Text Available On capitalism that is created under the pressure of globalization there are created many economic systems that derived into a new model: the asymmetric model created from propriety rights’ perspective and the influence of interest groups, an asymmetric model that is called “oligarchy”(1. For a better understanding of oligarchy we consider an oligarchic society, where the political power is in the hands of the producers of goods, that tend to protect their propriety rights, but this way they create entry barriers, destroying the propriety rights of future potential producers. Capitalism was and is stressed by the (deregulation phenomena created by the competition which is shaped through globalization. With ease we can go from (deregulating to oligarchic pressure, which from the globalization’s perspective can give birth to the lagging or decoupling in the global economic system. This paper researches these two cases and inserts them into the global framework to result the evolution of society’s members’ welfare.

Normal Anti-Invariant Submanifolds of Paraquaternionic Kähler Manifolds

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Novac-Claudiu Chiriac

2006-12-01

Full Text Available We introduce normal anti-invariant submanifolds of paraquaternionic Kähler manifolds and study the geometric structures induced on them. We obtain necessary and sufficient conditions for the integrability of the distributions defined on a normal anti-invariant submanifold. Also, we present characterizations of local (global anti-invariant products.

‘Small is Beautiful’, Analysing the Democratising Effect of Localism, Greater Regional Autonomy, Decentralisation and Constitutional Reform

Directory of Open Access Journals (Sweden)

Ben DUKE

2014-12-01

Full Text Available This paper seeks to provide a critical theoretical comparative review of the effect upon democracy, constitutional reform could have on new smaller states. This paper posits that it is an untried, untested assumption that democratisation will follow, if nation states’ populations choose constitutional reform. This paper also posits that social, economic, political, historical and cultural generic domains influence the drive for constitutional reform in very different ways globally. This paper intends to discuss the pressure for constitutional reform, from a globalisation perspective. This paper will demonstrate how globalisation itself is a significant causal factor, increasing the propensity towards constitutional reform of smaller states. This paper will also demonstrate that the EU anti-globalisation sentiment, asking for constitutional reform, is globally replicated elsewhere.

The Online Dissemination of Nature-Health Concepts: Lessons from Sentiment Analysis of Social Media Relating to "Nature-Deficit Disorder".

Science.gov (United States)

Palomino, Marco; Taylor, Tim; Göker, Ayse; Isaacs, John; Warber, Sara

2016-01-19

Evidence continues to grow supporting the idea that restorative environments, green exercise, and nature-based activities positively impact human health. Nature-deficit disorder, a journalistic term proposed to describe the ill effects of people's alienation from nature, is not yet formally recognized as a medical diagnosis. However, over the past decade, the phrase has been enthusiastically taken up by some segments of the lay public. Social media, such as Twitter, with its opportunities to gather "big data" related to public opinions, offers a medium for exploring the discourse and dissemination around nature-deficit disorder and other nature-health concepts. In this paper, we report our experience of collecting more than 175,000 tweets, applying sentiment analysis to measure positive, neutral or negative feelings, and preliminarily mapping the impact on dissemination. Sentiment analysis is currently used to investigate the repercussions of events in social networks, scrutinize opinions about products and services, and understand various aspects of the communication in Web-based communities. Based on a comparison of nature-deficit-disorder "hashtags" and more generic nature hashtags, we make recommendations for the better dissemination of public health messages through changes to the framing of messages. We show the potential of Twitter to aid in better understanding the impact of the natural environment on human health and wellbeing.

A possible constraint on regional precipitation intensity changes under global warming

DEFF Research Database (Denmark)

Gutowski, William J.; Kozak, K. A.; Arritt, R. W.

2007-01-01

Changes in daily precipitation versus intensity under a global warming scenario in two regional climate simulations of the United States show a well-recognized feature of more intense precipitation. More important, by resolving the precipitation intensity spectrum, the changes show a relatively...

GLOBALIZATION AND SMALL BUSINESSES AND ECONOMIES – CHALLENGES AND OPPORTUNITIES

Directory of Open Access Journals (Sweden)

NINKO KOSTOVSKI

2016-08-01

Full Text Available In this paper, we analyze the effect of globalization in general and from the viewpoint of the small and medium sized companies in the Republic of Macedonia, as a typical developing economy. Our survey of 100 managers and business owners from small and medium sized enterprises indicates that they tend to perceive the globalization with more conservative glasses as negative, or at the best, as a neutral phenomenon to their overall business prospects. However, to harvest the apparent opportunities of the globalization and to achieve the desired internationalization of their businesses, they call for intensive regional cooperation seeing it as a gateway to much harsher realms of the globalized market. The literature review and the examples from some other countries support these conservative standing of our managers and offer practical explanations why the approach towards the globalization is conservative and often even negative. Small business is important provider of new jobs, ideas and business concepts. However, with the opening of the global market it is a constant pursue for customers all around the world, having to meet their diverse and rapidly changing needs and facing extremely shortened delivery terms and product lifecycles. Many small companies, particularly from the developing countries are not adequately prepared to face the reality of this challenge. On the other hand, the big multinational companies receive more than hefty incentives to invest into the developing countries and that creates additional negative sentiments towards the globalization among the local companies.

Expansion of plants with Crassulacean Acid Metabolism under global environment change

Science.gov (United States)

Yu, K.; D'Odorico, P.; Collins, S. L.; Carr, D.

2016-12-01

The abundance of plants with Crassulacean Acid Metabolism (CAM) has increased in many drylands worldwide. This is hypothesized to occur because CAM plants store water, take up CO2 at night, exhibit photosynthetic plasticity, and have high water use efficiency. The increased dominance of CAM plants, however, also depends on their competitive relationship with other functional groups, an aspect of CAM plant sensitivity to global environmental change that has remained largely understudied. Here, we investigated the response of CAM plants and their competitive relationships with C3 and C4 plants under global environmental change. We focused on two pairs of CAM and non-CAM species, namely Cylindropuntia imbricata (a constitutive CAM species) and Bouteloua eriopoda (C4 grass), which co-occur in desert grasslands in northern Mexico, and invasive Mesembryanthemum crystallinum (a facultative CAM species) and Bromus mollis (a C3 invasive grass), which coexist in California's coastal grasslands. A set of growth chamber experiments under altered CO2 and water conditions show that C. imbricata outcompeted B. eriopoda under drought conditions, while in well-watered conditions B. eriopoda was a stronger competitor for soil water than C. imbricata. Under drought conditions a more positive response to CO2 enrichment by C. imbricata indirectly disfavored B. eriopoda, which suggests that interspecific competition can outweigh the favorable direct effect of CO2 enrichment on plant growth. A set of greenhouse experiments under water, N, and soil salinity manipulations showed that drought, N deposition, and/or increased soil salinity served as important drivers for success of M. crystallinum invasion, while B. mollis exerted strong competitive effects on M. crystallinum for light and soil nutrients in well-watered conditions. M. crystallinum switched from C3 photosynthesis to CAM photosynthesis as an adaptive strategy in response to moderate intensity of competition from B. mollis, in

Gauchos que lloran: masculinidades sentimentales en el imaginario criollista / Gauchos who Cry: Sentimental Masculinities in Criollo Imaginary

Directory of Open Access Journals (Sweden)

Ana Peluffo

2013-01-01

Full Text Available The present paper studies a canonical text in Argentinean literature, the Martín Fierro (1872-1878, by José Hernández. The objective is to explore, based on a debate on masculinity and nation,the sentimental side of criollo culture. Although Hernández’s gaucho is usually thought of as the archetype of a stoic masculinity that represses its emotions in order to fight wars at the border, this paper will show how that predominating notion undermines the tearful affective excesses constantly taking place in the text.

Attitudes of Crohn's Disease Patients: Infodemiology Case Study and Sentiment Analysis of Facebook and Twitter Posts.

Science.gov (United States)

Roccetti, Marco; Marfia, Gustavo; Salomoni, Paola; Prandi, Catia; Zagari, Rocco Maurizio; Gningaye Kengni, Faustine Linda; Bazzoli, Franco; Montagnani, Marco

2017-08-09

Data concerning patients originates from a variety of sources on social media. The aim of this study was to show how methodologies borrowed from different areas including computer science, econometrics, statistics, data mining, and sociology may be used to analyze Facebook data to investigate the patients' perspectives on a given medical prescription. To shed light on patients' behavior and concerns, we focused on Crohn's disease, a chronic inflammatory bowel disease, and the specific therapy with the biological drug Infliximab. To gain information from the basin of big data, we analyzed Facebook posts in the time frame from October 2011 to August 2015. We selected posts from patients affected by Crohn's disease who were experiencing or had previously been treated with the monoclonal antibody drug Infliximab. The selected posts underwent further characterization and sentiment analysis. Finally, an ethnographic review was carried out by experts from different scientific research fields (eg, computer science vs gastroenterology) and by a software system running a sentiment analysis tool. The patient feeling toward the Infliximab treatment was classified as positive, neutral, or negative, and the results from computer science, gastroenterologist, and software tool were compared using the square weighted Cohen's kappa coefficient method. The first automatic selection process returned 56,000 Facebook posts, 261 of which exhibited a patient opinion concerning Infliximab. The ethnographic analysis of these 261 selected posts gave similar results, with an interrater agreement between the computer science and gastroenterology experts amounting to 87.3% (228/261), a substantial agreement according to the square weighted Cohen's kappa coefficient method (w2K=0.6470). A positive, neutral, and negative feeling was attributed to 36%, 27%, and 37% of posts by the computer science expert and 38%, 30%, and 32% by the gastroenterologist, respectively. Only a slight agreement was

Optimization and anti-optimization of structures under uncertainty

National Research Council Canada - National Science Library

Elishakoff, Isaac; Ohsaki, Makoto

2010-01-01

The volume presents a collaboration between internationally recognized experts on anti-optimization and structural optimization, and summarizes various novel ideas, methodologies and results studied over 20 years...

Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis.

Directory of Open Access Journals (Sweden)

Young Bin Kim

Full Text Available In this paper, we present a method for predicting the value of virtual currencies used in virtual gaming environments that support multiple users, such as massively multiplayer online role-playing games (MMORPGs. Predicting virtual currency values in a virtual gaming environment has rarely been explored; it is difficult to apply real-world methods for predicting fluctuating currency values or shares to the virtual gaming world on account of differences in domains between the two worlds. To address this issue, we herein predict virtual currency value fluctuations by collecting user opinion data from a virtual community and analyzing user sentiments or emotions from the opinion data. The proposed method is straightforward and applicable to predicting virtual currencies as well as to gaming environments, including MMORPGs. We test the proposed method using large-scale MMORPGs and demonstrate that virtual currencies can be effectively and efficiently predicted with it.

Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis

Science.gov (United States)

Kim, Young Bin; Lee, Sang Hyeok; Kang, Shin Jin; Choi, Myung Jin; Lee, Jung; Kim, Chang Hun

2015-01-01

In this paper, we present a method for predicting the value of virtual currencies used in virtual gaming environments that support multiple users, such as massively multiplayer online role-playing games (MMORPGs). Predicting virtual currency values in a virtual gaming environment has rarely been explored; it is difficult to apply real-world methods for predicting fluctuating currency values or shares to the virtual gaming world on account of differences in domains between the two worlds. To address this issue, we herein predict virtual currency value fluctuations by collecting user opinion data from a virtual community and analyzing user sentiments or emotions from the opinion data. The proposed method is straightforward and applicable to predicting virtual currencies as well as to gaming environments, including MMORPGs. We test the proposed method using large-scale MMORPGs and demonstrate that virtual currencies can be effectively and efficiently predicted with it. PMID:26241496

Global crop yield response to extreme heat stress under multiple climate change futures

Science.gov (United States)

Deryng, D.; Conway, D.; Ramankutty, N.; Price, J.; Warren, R.

2014-12-01

Extreme heat stress during the crop reproductive period can be critical for crop productivity. Projected changes in the frequency and severity of extreme climatic events are expected to negatively impact crop yields and global food production. This study applies the global crop model PEGASUS to quantify, for the first time at the global scale, impacts of extreme heat stress on maize, spring wheat and soybean yields resulting from 72 climate change scenarios for the 21st century. Our results project maize to face progressively worse impacts under a range of RCPs but spring wheat and soybean to improve globally through to the 2080s due to CO2 fertilization effects, even though parts of the tropic and sub-tropic regions could face substantial yield declines. We find extreme heat stress at anthesis (HSA) by the 2080s (relative to the 1980s) under RCP 8.5, taking into account CO2 fertilization effects, could double global losses of maize yield (dY = -12.8 ± 6.7% versus -7.0 ± 5.3% without HSA), reduce projected gains in spring wheat yield by half (dY = 34.3 ± 13.5% versus 72.0 ± 10.9% without HSA) and in soybean yield by a quarter (dY = 15.3 ± 26.5% versus 20.4 ± 22.1% without HSA). The range reflects uncertainty due to differences between climate model scenarios; soybean exhibits both positive and negative impacts, maize is generally negative and spring wheat generally positive. Furthermore, when assuming CO2 fertilization effects to be negligible, we observe drastic climate mitigation policy as in RCP 2.6 could avoid more than 80% of the global average yield losses otherwise expected by the 2080s under RCP 8.5. We show large disparities in climate impacts across regions and find extreme heat stress adversely affects major producing regions and lower income countries.

Global crop yield response to extreme heat stress under multiple climate change futures

International Nuclear Information System (INIS)

Deryng, Delphine; Warren, Rachel; Conway, Declan; Ramankutty, Navin; Price, Jeff

2014-01-01

Extreme heat stress during the crop reproductive period can be critical for crop productivity. Projected changes in the frequency and severity of extreme climatic events are expected to negatively impact crop yields and global food production. This study applies the global crop model PEGASUS to quantify, for the first time at the global scale, impacts of extreme heat stress on maize, spring wheat and soybean yields resulting from 72 climate change scenarios for the 21st century. Our results project maize to face progressively worse impacts under a range of RCPs but spring wheat and soybean to improve globally through to the 2080s due to CO 2 fertilization effects, even though parts of the tropic and sub-tropic regions could face substantial yield declines. We find extreme heat stress at anthesis (HSA) by the 2080s (relative to the 1980s) under RCP 8.5, taking into account CO 2 fertilization effects, could double global losses of maize yield (ΔY = −12.8 ± 6.7% versus − 7.0 ± 5.3% without HSA), reduce projected gains in spring wheat yield by half (ΔY = 34.3 ± 13.5% versus 72.0 ± 10.9% without HSA) and in soybean yield by a quarter (ΔY = 15.3 ± 26.5% versus 20.4 ± 22.1% without HSA). The range reflects uncertainty due to differences between climate model scenarios; soybean exhibits both positive and negative impacts, maize is generally negative and spring wheat generally positive. Furthermore, when assuming CO 2 fertilization effects to be negligible, we observe drastic climate mitigation policy as in RCP 2.6 could avoid more than 80% of the global average yield losses otherwise expected by the 2080s under RCP 8.5. We show large disparities in climate impacts across regions and find extreme heat stress adversely affects major producing regions and lower income countries. (paper)

Discrete anti-gravity

International Nuclear Information System (INIS)

Noyes, H.P.; Starson, S.

1991-03-01

Discrete physics, because it replaces time evolution generated by the energy operator with a global bit-string generator (program universe) and replaces ''fields'' with the relativistic Wheeler-Feynman ''action at a distance,'' allows the consistent formulation of the concept of signed gravitational charge for massive particles. The resulting prediction made by this version of the theory is that free anti-particles near the surface of the earth will ''fall'' up with the same acceleration that the corresponding particles fall down. So far as we can see, no current experimental information is in conflict with this prediction of our theory. The experiment crusis will be one of the anti-proton or anti-hydrogen experiments at CERN. Our prediction should be much easier to test than the small effects which those experiments are currently designed to detect or bound. 23 refs

Palliative care in Africa: a global challenge.

Science.gov (United States)

Ntizimira, Christian R; Nkurikiyimfura, Jean Luc; Mukeshimana, Olive; Ngizwenayo, Scholastique; Mukasahaha, Diane; Clancy, Clare

2014-01-01

We are often asked what challenges Rwanda has faced in the development of palliative care and its integration into the healthcare system. In the past, patients have been barred from accessing strong analgesics to treat moderate to severe pain, but thanks to health initiatives, this is slowly changing. Rwanda is an example of a country where only a few years ago, access to morphine was almost impossible. Albert Einsten said 'in the middle of difficulty lies opportunity' and this sentiment could not be more relevant to the development of palliative care programmes. Through advocacy, policy, and staunch commitment to compassion, Rwandan healthcare workers are proving how palliative care can be successfully integrated into a healthcare system. As a global healthcare community, we should be asking what opportunities exist to do this across the African continent. Champions of palliative care have a chance to forge lasting collaborations between international experts and African healthcare workers. This global network could not only advocate for palliative care programmes but it would also help to create a culture where palliative care is viewed as a necessary part of all healthcare systems.

Future ecological studies of Brazilian headwater streams under global-changes

Directory of Open Access Journals (Sweden)

Marcos Callisto

Full Text Available This paper results from discussions triggered during the "Stream Ecology Symposium" that took place at the XIII Congress of the Brazilian Society of Limnology in September of 2011 in Natal, Brazil. Based on our experiences, we have raised several questions regarding ecological studies of headwater streams facing threats under global-changes and proposed numerous subjects to be addressed in future studies in Brazil. These studies deal with the necessity of knowing species biology and the elaboration of models to assess changes (which implies the availability of time-series or large-scale data sets; the ecology of riparian zones and the interchange of materials and energy across the land-water boundaries; forest conversions and standardized sampling strategies and data treatment to assess global change.

Help Wanted: American Drone Program Needs Multifaceted Support to be Effective

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S. Hall

2014-12-01

Full Text Available The U.S. drone program in Pakistan faces strong resistance in Pakistan. Because the program solely seeks to eliminate terrorist groups and leaders through bombing campaigns, with no built in social support, the local population’s anti-American sentiment has reached the highest level in history. This angry mood against U.S. drone programs is spreading throughout the Islamic world. To counter this anti-American sentiment, and increase the drone program’s effectiveness, the U.S. must invest in multifaceted, socio-economic support efforts to educate the population and rebuild the gratuity, trust, and commitment of Pakistan’s people to the “War on Terror.”

The discourse of liberation: Frames used in characterising the gay liberation movement in two South African newspapers

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Lauren Danger Mongie

2015-09-01

Full Text Available This article reports on the quantitative findings of a study that straddles the applied linguistic field of critical discourse analysis and a sociolinguistic field recently referred to as “queer linguistics”. Drawing on a quantitative method of analysis, the study investigates the linguistic framing of LGBT mobilisation in two South African newspapers, City Press and the Mail & Guardian, across a period of almost 30 years. It aims to identify the characteristics of the discourses that topicalise the gay[1] liberation movement in order to investigate the ways in which linguistic means have been used in articulating the need and the right to liberation and how arguments against the gay liberation movement have been framed, reframed and counterframed in South African media. The study’s findings revealed that a number of frames, including ‘liberation’, ‘rights’ and ‘victimisation’, reoccurred in the framing of arguments for the gay liberation movement throughout the data collection period in both corpora, and while City Press primarily used these frames to express anti-gay sentiments, the Mail & Guardian primarily used these frames to express pro-gay sentiments. The findings also revealed that a number of frames, including ‘religion’, ‘morality’ and ‘nature’, reoccurred in the framing of arguments against the gay liberation movement, and again while City Press primarily used these frames to express anti-gay sentiments, the Mail & Guardian primarily used these frames to express pro-gay sentiments. Finally, the findings revealed that a single frame such as “religion” was typically used to express both pro- and anti-gay sentiments, bringing to light the important role that counterframing plays in bringing about social transformation.[1] The word “gay” is used as a hypernym in this article as this is a reflection of the way in which the liberation movement was typically topicalised in the data.

Neural Global Pattern Similarity Underlies True and False Memories.

Science.gov (United States)

Ye, Zhifang; Zhu, Bi; Zhuang, Liping; Lu, Zhonglin; Chen, Chuansheng; Xue, Gui

2016-06-22

The neural processes giving rise to human memory strength signals remain poorly understood. Inspired by formal computational models that posit a central role of global matching in memory strength, we tested a novel hypothesis that the strengths of both true and false memories arise from the global similarity of an item's neural activation pattern during retrieval to that of all the studied items during encoding (i.e., the encoding-retrieval neural global pattern similarity [ER-nGPS]). We revealed multiple ER-nGPS signals that carried distinct information and contributed differentially to true and false memories: Whereas the ER-nGPS in the parietal regions reflected semantic similarity and was scaled with the recognition strengths of both true and false memories, ER-nGPS in the visual cortex contributed solely to true memory. Moreover, ER-nGPS differences between the parietal and visual cortices were correlated with frontal monitoring processes. By combining computational and neuroimaging approaches, our results advance a mechanistic understanding of memory strength in recognition. What neural processes give rise to memory strength signals, and lead to our conscious feelings of familiarity? Using fMRI, we found that the memory strength of a given item depends not only on how it was encoded during learning, but also on the similarity of its neural representation with other studied items. The global neural matching signal, mainly in the parietal lobule, could account for the memory strengths of both studied and unstudied items. Interestingly, a different global matching signal, originated from the visual cortex, could distinguish true from false memories. The findings reveal multiple neural mechanisms underlying the memory strengths of events registered in the brain. Copyright © 2016 the authors 0270-6474/16/366792-11$15.00/0.

ANTI-TERROR POLICY OF UZBEKISTAN IN THE FRAMEWORK OF THE REGIONAL ANTI-TERRORIST POLICY OF THE SCO

Directory of Open Access Journals (Sweden)

С П Базылева

2017-12-01

Full Text Available The beginning of the XXI century was marked by a number of serious problems, including cancer, world hunger, environmental problems and increasing every year the problem of global terrorism, which poses a great threat to the security of the modern multipolar world. Uzbekistan today occupies a firm position in fight against terrorist threat. The principled position of Uzbekistan in the fight against terrorism is that “no country should exclude their participation in the fight against global terrorism, there must be no transit zones and "green corridors" for terrorist organizations”. The Central Asian region is one of the most vulnerable, because it is necessary to pay special attention to the strategy of the anti-terrorist security of the countries included in the structure of the Central Asian region. In this article, we consider the anti-terrorist policy of Uzbekistan in the framework of the regional anti-terrorist policy of the SCO.

A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews

Science.gov (United States)

Zhang, Liujie; Zhou, Yanquan; Duan, Xiuyu; Chen, Ruiqi

2018-03-01

Multi-label sentiment classification on customer reviews is a practical challenging task in Natural Language Processing. In this paper, we propose a hierarchical multi-input and output model based bi-directional recurrent neural network, which both considers the semantic and lexical information of emotional expression. Our model applies two independent Bi-GRU layer to generate part of speech and sentence representation. Then the lexical information is considered via attention over output of softmax activation on part of speech representation. In addition, we combine probability of auxiliary labels as feature with hidden layer to capturing crucial correlation between output labels. The experimental result shows that our model is computationally efficient and achieves breakthrough improvements on customer reviews dataset.

Does Identification With Rwanda Increase Reconciliation Sentiments Between Genocide Survivors and Non-Victims? The Mediating Roles of Perceived Intergroup Similarity and Self-Esteem During Commemorations

Directory of Open Access Journals (Sweden)

Clémentine Kanazayire

2014-12-01

Full Text Available A questionnaire survey (N = 247 investigated the influence of identification with the Rwandan nation on reconciliation sentiments between members of the survivor and of the non-victim groups of the 1994 genocide in Rwanda. Results showed that, whereas the two groups did not differ in their level of identification with the nation, members of the non-victim group were more willing to reconcile than members of the survivor group. Perceived intergroup similarity mediated the effect of national identification on reconciliation sentiment for both groups, but this effect was stronger among non-victims. Finally, self-esteem during commemorations also mediated this effect, but only among non-victims. We discuss the importance of people’s motivation to reconcile with out-group members in post-genocidal contexts in light of the common in-group identity model (Gaertner & Dovidio, 2000 as well as the needs-based model of intergroup reconciliation (Nadler & Schnabel, 2008.

Early anti-correlated BOLD signal changes of physiologic origin.

Science.gov (United States)

Bright, Molly G; Bianciardi, Marta; de Zwart, Jacco A; Murphy, Kevin; Duyn, Jeff H

2014-02-15

Negative BOLD signals that are synchronous with resting state fluctuations have been observed in large vessels in the cortical sulci and surrounding the ventricles. In this study, we investigated the origin of these negative BOLD signals by applying a Cued Deep Breathing (CDB) task to create transient hypocapnia and a resultant global fMRI signal decrease. We hypothesized that a global stimulus would amplify the effect in large vessels and that using a global negative (vasoconstrictive) stimulus would test whether these voxels exhibit either inherently negative or simply anti-correlated BOLD responses. Significantly anti-correlated, but positive, BOLD signal changes during respiratory challenges were identified in voxels primarily located near edges of brain spaces containing CSF. These positive BOLD responses occurred earlier than the negative CDB response across most of gray matter voxels. These findings confirm earlier suggestions that in some brain regions, local, fractional changes in CSF volume may overwhelm BOLD-related signal changes, leading to signal anti-correlation. We show that regions with CDB anti-correlated signals coincide with most, but not all, of the regions with negative BOLD signal changes observed during a visual and motor stimulus task. Thus, the addition of a physiological challenge to fMRI experiments can help identify which negative BOLD signals are passive physiological anti-correlations and which may have a putative neuronal origin. Published by Elsevier Inc.

Anti-Counterfeiting Quick Response Code with Emission Color of Invisible Metal-Organic Frameworks as Encoding Information.

Science.gov (United States)

Wang, Yong-Mei; Tian, Xue-Tao; Zhang, Hui; Yang, Zhong-Rui; Yin, Xue-Bo

2018-06-08

Counterfeiting is a global epidemic that is compelling the development of new anti-counterfeiting strategy. Herein, we report a novel multiple anti-counterfeiting encoding strategy of invisible fluorescent quick response (QR) codes with emission color as information storage unit. The strategy requires red, green, and blue (RGB) light-emitting materials for different emission colors as encrypting information, single excitation for all of the emission for practicability, and ultraviolet (UV) excitation for invisibility under slight. Therefore, RGB light-emitting nanoscale metal-organic frameworks (NMOFs) are designed as inks to construct the colorful light-emitting boxes for information encrypting, while three black vertex boxes were used for positioning. Full-color emissions are obtained by mixing the trichromatic NMOFs inks through inkjet printer. The encrypting information capacity is easily adjusted by the number of light-emitting boxes with the infinite emission colors. The information is decoded with specific excitation light at 275 nm, making the QR codes invisible under daylight. The composition of inks, invisibility, inkjet printing, and the abundant encrypting information all contribute to multiple anti-counterfeiting. The proposed QR codes pattern holds great potential for advanced anti-counterfeiting.

Global Water Scarcity Assessment under Post-SRES Scenarios

Science.gov (United States)

Hanasaki, N.; Fujimori, S.

2011-12-01

A large number of future projections contributed to the fourth Assessment Report of IPCC were based on Special Report on Emission Scenarios (SRES). Processes toward the fifth Assessment Report are under way, and post-SRES scenarios, called Shared Socio-economic Pathways (SSP) are being prepared. One of the key challenges of SSP is provision of detailed socio-economic scenarios compared to SRES for impact, adaptation and vulnerability studies. In this study, a comprehensive global water scarcity assessment was conducted, using a state of the art global water resources model H08 (Hanasaki et al., 2008a, 2008b, 2010). We used a prototype of SSP developed by National Institute for Environmental Studies, Japan. Two sets of socio economic scenarios and two sets of climate scenarios were prepared to run H08 for the period 2001-2100. Socio-economic scenarios include Business As Usual and High Mitigation Capacity. Climate scenarios include Reference and Mitigation which stabilizes green house gas concentration at a certain level. We analyzed the simulation results of four combinations, particularly focusing on the sensitivity of socio-economic scenarios to major water resources indices.

Censoring the Press: A Barometer of Government Tolerance for Anti-regime Dissent under Authoritarian Rule

Directory of Open Access Journals (Sweden)

Elizabeth Ann Stein

2016-01-01

Full Text Available This paper proposes that dissident leaders aiming to build mass opposition movements follow the mainstream press to help them gauge government tolerance for anti-government mass actions in repressive authoritarian regimes. Under conditions of censorship, media–state interactions serve as a barometer of the government’s disposition toward and capacity to impede public displays of dissent. Observing trends in coverage and the government’s reaction to this coverage helps activist leaders assess when it should be safest to plan anti-government mass actions, such as demonstrations, marches, or strikes. Using original data derived from coding content from the Brazilian newspaper Folha de São Paulo over the period of 1974–1982, I test whether opposition mass actions followed trends in taboo content and government treatment of the press during the period of political liberalization of Brazil’s military regime.

CERN anti-fraud policy

CERN Multimedia

2013-01-01

In 2011, a working group on improved fraud prevention and management was established. The group was composed of the Director of Administration and General Infrastructure, the Head of the Human Resources Department, and the Heads of the Legal Service and Internal Audit. It recommended the adoption of a global fraud prevention and management policy.   The global fraud prevention and management policy was implemented through the CERN Anti-Fraud Policy, which was endorsed by the Enlarged Directorate in May 2012 and approved by the Director-General for entry into force on 1 January 2013. The CERN Anti-Fraud Policy defines the Organization’s policy in matters of fraud.  CERN has a zero tolerance approach towards fraud, as it would compromise the accomplishment of its objectives and undermine its functioning, credibility and reputation. The policy also states CERN’s commitment to the prevention, identification and investigation of fraud. All CERN contributors have a key rol...

What's Wrong with the Global Slavery Index?

Directory of Open Access Journals (Sweden)

Anne T Gallagher

2017-04-01

Full Text Available The Global Slavery Index (GSI, which has been produced by the Walk Free Foundation in 2013, 2014 and 2016, seeks to calculate the number of victims of human trafficking (or ‘modern slavery’ in each country and to assess and rank government responses. Using the latest iteration of the Index, this article examines each of the three elements (vulnerability measurement; prevalence measurement and response measurement, making some preliminary findings about the quality of the methodology and its application under each heading. It concludes with a consideration of two broader issues: (i the conspicuous lack of critical engagement with the Index; and (ii what the Index reveals about the changing face of anti-trafficking/anti-slavery work—most particularly, the growing involvement of metrics-focused strategic philanthropy in defining the ‘problem’ and directing responses.

Assessing carbon dioxide removal through global and regional ocean alkalinization under high and low emission pathways

Science.gov (United States)

Lenton, Andrew; Matear, Richard J.; Keller, David P.; Scott, Vivian; Vaughan, Naomi E.

2018-04-01

Atmospheric carbon dioxide (CO2) levels continue to rise, increasing the risk of severe impacts on the Earth system, and on the ecosystem services that it provides. Artificial ocean alkalinization (AOA) is capable of reducing atmospheric CO2 concentrations and surface warming and addressing ocean acidification. Here, we simulate global and regional responses to alkalinity (ALK) addition (0.25 PmolALK yr-1) over the period 2020-2100 using the CSIRO-Mk3L-COAL Earth System Model, under high (Representative Concentration Pathway 8.5; RCP8.5) and low (RCP2.6) emissions. While regionally there are large changes in alkalinity associated with locations of AOA, globally we see only a very weak dependence on where and when AOA is applied. On a global scale, while we see that under RCP2.6 the carbon uptake associated with AOA is only ˜ 60 % of the total, under RCP8.5 the relative changes in temperature are larger, as are the changes in pH (140 %) and aragonite saturation state (170 %). The simulations reveal AOA is more effective under lower emissions, therefore the higher the emissions the more AOA is required to achieve the same reduction in global warming and ocean acidification. Finally, our simulated AOA for 2020-2100 in the RCP2.6 scenario is capable of offsetting warming and ameliorating ocean acidification increases at the global scale, but with highly variable regional responses.

Libro de Mano: "Novela Política e Sentimental", um pasquim manuscrito

Directory of Open Access Journals (Sweden)

Francisca L. Nogueira de Azevedo

2010-01-01

Full Text Available Neste artigo as autoras analisam um documento depositado na seção de manuscritos da Biblioteca Nacional no Rio de Janeiro, na pasta de "jornais manuscritos", intitulado "Novella pollítica e sentimental"; descrição de factos dos tempos da Revolução e Campanha Oriental e da Colônia de Sacramento 1810-1823. Não consta a autoria, tampouco a data de produção do documento. O texto tem 51 páginas manuscritas e é dividido em três partes, e pressupomos que seja material de propaganda política em favor da monarquia espanhola. Este artigo destaca, inicialmente, em que medida os panfletos manuscritos serviram às elites coloniais para a mobilização política das camadas populares iletradas. O ponto central é a análise da narrativa novelesca, no sentido de perceber os elementos discursivos utilizados como persuasão em defesa da Espanha.

Anti-Neuroblastoma Activity of Gold Nanorods Bound with GD2 Monoclonal Antibody under Near-Infrared Laser Irradiation

International Nuclear Information System (INIS)

Peng, Ching-An; Wang, Chung-Hao

2011-01-01

High-risk neuroblastoma is one of the most common deaths in pediatric oncology. Current treatment of this disease involves a coordinated sequence of chemotherapy, surgery, and radiation. Further advances in therapy will require the targeting of tumor cells in a more selective and efficient way so that survival can be improved without substantially increasing toxicity. To achieve tumor-selective delivery, disialoganglioside (GD2) expressed by almost all neuroblastoma tumors represents a potential molecular target that can be exploited for tumor-selective delivery. In this study, GD2 monoclonal antibody (anti-GD2) was conjugated to gold nanorods (GNRs) which are one of anisotropic nanomaterials that can absorb near-infrared (NIR) laser light and convert it to energy for photothermolysis of tumor cells. Thiolated chitosan, due to its biocompatibility, was used to replace cetyltrimethylammonium bromide (CTAB) originally used in the synthesis of gold nanorods. In order to specifically target GD2 overexpressed on the surface of neuroblastoma stNB-V1 cells, anti-GD2 was conjugated to chitosan modified GNRs (CGNRs). To examine the fate of CGNRs conjugated with anti-GD2 after incubation with neuroblastoma cells, rhadoamine B was labeled on CGNRs functionalized with anti-GD2. Our results illustrated that anti-GD2-conjugated CGNRs were extensively endocytosed by GD2 + stNB-V1 neuroblastoma cells via antibody-mediated endocytosis. In addition, we showed that anti-GD2 bound CGNRs were not internalized by GD2 − SH-SY5Y neuroblastoma cells. After anti-GD2-linked CGNRs were incubated with neuroblatoma cells for six hours, the treated cells were further irradiated with 808 nm NIR laser. Post-NIR laser exposure, when examined by calcein-AM dye, stNB-V1 cells all underwent necrosis, while non-GD2 expressing SH-SY5Y cells all remained viable. Based on the in vitro study, CGNRs bound with anti-GD2 has the potential to be utilized as a therapeutic thermal coupling agent that generates

Stochastic Delay Population Dynamics under Regime Switching: Global Solutions and Extinction

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Zheng Wu

2013-01-01

Full Text Available This paper is concerned with a delay Lotka-Volterra model under regime switching diffusion in random environment. By using generalized Itô formula, Gronwall inequality and Young’s inequality, some sufficient conditions for existence of global positive solutions and stochastically ultimate boundedness are obtained, respectively. Finally, an example is given to illustrate the main results.

Dermatomyositis with anti-TIF-1γ antibodies as a presenting symptom of underlying triple-negative breast cancer: a case report

International Nuclear Information System (INIS)

Kubeček, Ondřej; Soukup, Tomáš; Paulík, Adam; Kopecký, Jindřich

2016-01-01

Dermatomyositis is an autoimmune myopathy characterized by proximal muscle weakness, muscle inflammation, and typical skin findings. It is a rare disease with an incidence of ~1/100 000. About 15–30 % of adult-onset cases are caused by underlying malignancy and dermatomyositis can be the first symptom of undiagnosed cancer, mainly in the case of anti-transcription intermediary factor 1γ (anti-TIF-1γ) antibodies presence. TIF-1γ is a transcriptional cofactor which is implicated in TGFβ signaling pathway that controls cell proliferation, differentiation, apoptosis, and tumorigenesis. Its expression was shown to be associated with younger age, higher tumor grade, more estrogen receptor negativity, tumors larger than 2 cm, and tendency towards poor outcome in early breast cancer. No association between anti-TIF-1γ antibodies and prognosis has been proposed yet. We report a case of a 43-year-old premenopausal woman presenting with the symptoms of systemic rheumatic disease, the most prominent being a typical skin rash and muscle pain. After a series of investigations, the patient was diagnosed with anti-TIF-1γ positive dermatomyositis and concurrent triple-negative breast cancer (cT1c N3c M0) as an underlying cause. Immediate intravenous corticosteroid therapy relieved the symptoms and enabled anticancer therapy to be commenced. Considering the tumor stage, neoadjuvant therapy with 4 courses of AC (Doxorubicin/Cyclophosphamide) followed by 4 courses of Paclitaxel/Carboplatin was administered. However, no tumor regression was documented and radiotherapy was chosen as the definitive treatment. Early detection of anti-TIF-1γ autoantibodies can contribute to a rapid diagnosis of tumor-associated dermatomyositis and enable immediate anticancer treatment. We demonstrate the emerging role of anti-TIF-1γ antibodies in the diagnostics of tumor-associated dermatomyositis. Furthermore, we propose a potential role of anti-TIF-1γ antibodies as a prognostic marker in early

Use of local and global limit load solutions for plates with surface cracks under tension

Energy Technology Data Exchange (ETDEWEB)

Lei, Y. [British Energy Generation Ltd, Barnett Way, Bamwood, Gloucester GL4 3RS (United Kingdom)], E-mail: yuebao.lei@british-energy.com

2007-09-15

Some available experimental results for the ductile failure of plates with surface cracks under tension are reviewed. The response of crack driving force, J, and the ligament strain near the local and global limit loads are investigated by performing elastic-perfectly plastic finite element (FE) analysis of a plate with a semi-elliptical crack under tension. The results show that a ligament may survive until the global collapse load is reached when the average ligament strain at the global collapse load, which depends on the uniaxial strain corresponding to the flow stress of the material and the crack geometry, is less than the true fracture strain of the material obtained from uniaxial tension tests. The FE analysis shows that ligament yielding corresponding to the local limit load has little effect on J and the average ligament strain, whereas approach to global collapse corresponds to a sharp increase in both J and the average ligament strain. The prediction of the FE value of J using the reference stress method shows that the global limit load is more relevant to J-estimation than the local one.

Use of local and global limit load solutions for plates with surface cracks under tension

International Nuclear Information System (INIS)

Lei, Y.

2007-01-01

Some available experimental results for the ductile failure of plates with surface cracks under tension are reviewed. The response of crack driving force, J, and the ligament strain near the local and global limit loads are investigated by performing elastic-perfectly plastic finite element (FE) analysis of a plate with a semi-elliptical crack under tension. The results show that a ligament may survive until the global collapse load is reached when the average ligament strain at the global collapse load, which depends on the uniaxial strain corresponding to the flow stress of the material and the crack geometry, is less than the true fracture strain of the material obtained from uniaxial tension tests. The FE analysis shows that ligament yielding corresponding to the local limit load has little effect on J and the average ligament strain, whereas approach to global collapse corresponds to a sharp increase in both J and the average ligament strain. The prediction of the FE value of J using the reference stress method shows that the global limit load is more relevant to J-estimation than the local one

A stochastic global identification framework for aerospace structures operating under varying flight states

Science.gov (United States)

Kopsaftopoulos, Fotis; Nardari, Raphael; Li, Yu-Hung; Chang, Fu-Kuo

2018-01-01

In this work, a novel data-based stochastic "global" identification framework is introduced for aerospace structures operating under varying flight states and uncertainty. In this context, the term "global" refers to the identification of a model that is capable of representing the structure under any admissible flight state based on data recorded from a sample of these states. The proposed framework is based on stochastic time-series models for representing the structural dynamics and aeroelastic response under multiple flight states, with each state characterized by several variables, such as the airspeed, angle of attack, altitude and temperature, forming a flight state vector. The method's cornerstone lies in the new class of Vector-dependent Functionally Pooled (VFP) models which allow the explicit analytical inclusion of the flight state vector into the model parameters and, hence, system dynamics. This is achieved via the use of functional data pooling techniques for optimally treating - as a single entity - the data records corresponding to the various flight states. In this proof-of-concept study the flight state vector is defined by two variables, namely the airspeed and angle of attack of the vehicle. The experimental evaluation and assessment is based on a prototype bio-inspired self-sensing composite wing that is subjected to a series of wind tunnel experiments under multiple flight states. Distributed micro-sensors in the form of stretchable sensor networks are embedded in the composite layup of the wing in order to provide the sensing capabilities. Experimental data collected from piezoelectric sensors are employed for the identification of a stochastic global VFP model via appropriate parameter estimation and model structure selection methods. The estimated VFP model parameters constitute two-dimensional functions of the flight state vector defined by the airspeed and angle of attack. The identified model is able to successfully represent the wing

The role stratification on Indian ocean mixing under global warming

Science.gov (United States)

Praveen, V.; Valsala, V.; Ravindran, A. M.

2017-12-01

The impact of changes in Indian ocean stratification on mixing under global warming is examined. Previous studies on global warming and associated weakening of winds reported to increase the stratification of the world ocean leading to a reduction in mixing, increased acidity, reduced oxygen and there by a reduction in productivity. However this processes is not uniform and are also modulated by changes in wind pattern of the future. Our study evaluate the role of stratification and surface fluxes on mixing focusing northern Indian ocean. A dynamical downscaling study using Regional ocean Modelling system (ROMS) forced with stratification and surface fluxes from selected CMIP5 models are presented. Results from an extensive set of historical and Representative Concentration Pathways 8.5 (rcp8.5) scenario simulations are used to quantify the distinctive role of stratification on mixing.

Two faces of global open society

Directory of Open Access Journals (Sweden)

Cvetićanin Neven

2008-01-01

Full Text Available The Essay considers 'the rule' of the so called post-civil political centre that corresponds to the familiar concept of open society, questioning the good as well as the bad sides of such 'rule'. The research is in the first place about global open society stability and attention is addressed to its present enemies - from terrorism, over organized crime, all the way to the so called local legitimates that are confronting the universal and global legitimates represented by the followers of the open society from the post civil political centre area. The Essay presents the debate with Fukuyama's thesis about the 'end of history' considering that open society, i.e. global post civil political centre has visible enemies who do not allow for dialectics of history to stand still as Fukuyama believed. Instead of Fukuyama's 'end of history' the Essay comes to the conclusion that present global situation is marked by post-modern opposition of liberal-democratic post civil centre and extreme anti civil margins, with reference to the opposition of open society and its enemies, which will put under limits further steps of history towards new socio-historical forms.

KĀFIR PRIDE: AN EXAMINATION OF THE RECENT APPARENT RISE IN AUSTRALIAN ANTI-ISLAMIC ACTIVITY AND THE CHALLENGES IT PRESENTS FOR NATIONAL SECURITY

Directory of Open Access Journals (Sweden)

Douglas Fry

2016-03-01

Full Text Available Multiple high-profile instances of anti-Islamic activity in Australia throughout 2015 – for example, the Reclaim Australia rallies in April and July, and the establishment of an anti-Islamic federal political party – is in keeping with increased Islamophobia observed in other western nations. While a key driving force behind this phenomenon is the September 11, 2001 terrorist attacks in the United States, ongoing jihadi violence – particularly atrocities committed by or on behalf of Islamic State –has served to reinforce anti-Islamic sentiment. Although objections to Islam are ostensibly cultural and religious, the prejudiced nature of Islamophobia essentially operates as racism. Emergent discourses about Islamic culture – for example, fears of Sharia law being imposed on western society – have positioned Muslims as an “enemy” who endanger western cultural values, and even present an existential threat. Accordingly, the risk of violence from anti-Islamic elements is not insignificant. To that end, this paper examines the range of security issues arising from Australian Islamophobic activity in two parts. First, it provides historical and cultural context for contemporary Islamophobia, noting the parallels and overlap with similar movements in the West. The primary themes promoted by anti-Islamic groups, and the manner by which they interact with audiences, are also analysed, noting the heavy emphasis on online communication, and how this translates to offline activities. Second, it will examine the types of potential or actual security risks that anti-Islamic activity presents to Australian authorities, describing a spectrum of increasing intensity that incorporates communication, physical violence, radicalisation and terrorism.

The Online Dissemination of Nature–Health Concepts: Lessons from Sentiment Analysis of Social Media Relating to “Nature-Deficit Disorder”

Science.gov (United States)

Palomino, Marco; Taylor, Tim; Göker, Ayse; Isaacs, John; Warber, Sara

2016-01-01

Evidence continues to grow supporting the idea that restorative environments, green exercise, and nature-based activities positively impact human health. Nature-deficit disorder, a journalistic term proposed to describe the ill effects of people’s alienation from nature, is not yet formally recognized as a medical diagnosis. However, over the past decade, the phrase has been enthusiastically taken up by some segments of the lay public. Social media, such as Twitter, with its opportunities to gather “big data” related to public opinions, offers a medium for exploring the discourse and dissemination around nature-deficit disorder and other nature–health concepts. In this paper, we report our experience of collecting more than 175,000 tweets, applying sentiment analysis to measure positive, neutral or negative feelings, and preliminarily mapping the impact on dissemination. Sentiment analysis is currently used to investigate the repercussions of events in social networks, scrutinize opinions about products and services, and understand various aspects of the communication in Web-based communities. Based on a comparison of nature-deficit-disorder “hashtags” and more generic nature hashtags, we make recommendations for the better dissemination of public health messages through changes to the framing of messages. We show the potential of Twitter to aid in better understanding the impact of the natural environment on human health and wellbeing. PMID:26797628

The Online Dissemination of Nature–Health Concepts: Lessons from Sentiment Analysis of Social Media Relating to “Nature-Deficit Disorder”

Directory of Open Access Journals (Sweden)

Marco Palomino

2016-01-01

Full Text Available Evidence continues to grow supporting the idea that restorative environments, green exercise, and nature-based activities positively impact human health. Nature-deficit disorder, a journalistic term proposed to describe the ill effects of people’s alienation from nature, is not yet formally recognized as a medical diagnosis. However, over the past decade, the phrase has been enthusiastically taken up by some segments of the lay public. Social media, such as Twitter, with its opportunities to gather “big data” related to public opinions, offers a medium for exploring the discourse and dissemination around nature-deficit disorder and other nature–health concepts. In this paper, we report our experience of collecting more than 175,000 tweets, applying sentiment analysis to measure positive, neutral or negative feelings, and preliminarily mapping the impact on dissemination. Sentiment analysis is currently used to investigate the repercussions of events in social networks, scrutinize opinions about products and services, and understand various aspects of the communication in Web-based communities. Based on a comparison of nature-deficit-disorder “hashtags” and more generic nature hashtags, we make recommendations for the better dissemination of public health messages through changes to the framing of messages. We show the potential of Twitter to aid in better understanding the impact of the natural environment on human health and wellbeing.

Antioxidant Property of Jobelyn as the Possible Mechanism Underlying its Anti-amnesic Activity in Rodents

Directory of Open Access Journals (Sweden)

Solomon Umukoro

2013-02-01

Full Text Available Introduction: Amnesia or loss of memory is the cardinal hallmark of Alzheimer’s disease (AD, a progressive neurodegenerative disorder associated with ageing process. Although, AD had been discovered over a century ago, drugs which could cure or halt the progression of the disease are yet to see the light of the day. However, there has been a growing interest in the use of phytomedicines with multipronged mechanisms of action that could target various aspects of the pathologies of AD. Jobelyn (JB is a potent antioxidant African polyherbal formulation with active components that have been acclaimed to show neuroprotection. This investigation was carried out to evaluate whether JB has anti-amnesic and antioxidant activities. Methods: The alteration of alternation behavior in the Y-maze paradigm was utilized as the test for memory function in mice.  The effect of JB on acetylcholinesterase (AChE activity, malondialdehyde (MDA level and the concentrations of glutathione (GSH in the frontal cortex and hippocampus were assessed in rats as means of providing insight into the mechanism underlying its anti-amnesic activity. The animals were given JB (1, 2.5 or 5mg/kg, i.p. daily for 7 days before the biochemical assays or test for memory functions were carried out.  Results: JB was found to produce a signi.cant increase in the level of alternation behavior compared with the control, suggesting anti-amnesic activity. Also, JB reversed the memory impairment induced by scopolamine, which further indicates anti-amnesic property. Furthermore, JB demonstrated a signi.cant inhibition of MDA formation in the frontal cortex and hippocampus of rats, indicating antioxidant property.  In addition, it increased the defense armory of the brain tissues, as it signi.cantly increased the concentrations of GSH in the frontal cortex and hippocampus of rats. However, JB did not demonstrate any inhibitory effect against AChE activity in the frontal cortex and hippocampus

Social media analysis during political turbulence.

Science.gov (United States)

Antonakaki, Despoina; Spiliotopoulos, Dimitris; V Samaras, Christos; Pratikakis, Polyvios; Ioannidis, Sotiris; Fragopoulou, Paraskevi

2017-01-01

Today, a considerable proportion of the public political discourse on nationwide elections proceeds in Online Social Networks. Through analyzing this content, we can discover the major themes that prevailed during the discussion, investigate the temporal variation of positive and negative sentiment and examine the semantic proximity of these themes. According to existing studies, the results of similar tasks are heavily dependent on the quality and completeness of dictionaries for linguistic preprocessing, entity discovery and sentiment analysis. Additionally, noise reduction is achieved with methods for sarcasm detection and correction. Here we report on the application of these methods on the complete corpus of tweets regarding two local electoral events of worldwide impact: the Greek referendum of 2015 and the subsequent legislative elections. To this end, we compiled novel dictionaries for sentiment and entity detection for the Greek language tailored to these events. We subsequently performed volume analysis, sentiment analysis, sarcasm correction and topic modeling. Results showed that there was a strong anti-austerity sentiment accompanied with a critical view on European and Greek political actions.

The State Made Me Do It

DEFF Research Database (Denmark)

Axelsen, David Vestergaard

2013-01-01

an independent argument for cosmopolitanism. Instead it grants a number of key anti-cosmopolitan premises, and argues that even if we accept these, we have good reasons to deny the conclusions. More specifically, the article attempts to show that national identity and anti-cosmopolitan sentiments are to a non...

Free Vibration Study of Anti-Symmetric Angle-Ply Laminated Plates under Clamped Boundary Conditions

Science.gov (United States)

Viswanathan, K. K.; Karthik, K.; Sanyasiraju, Y. V. S. S.; Aziz, Z. A.

2016-11-01

Two type of numerical approach namely, Radial Basis Function and Spline approximation, used to analyse the free vibration of anti-symmetric angle-ply laminated plates under clamped boundary conditions. The equations of motion are derived using YNS theory under first order shear deformation. By assuming the solution in separable form, coupled differential equations obtained in term of mid-plane displacement and rotational functions. The coupled differential is then approximated using Spline function and radial basis function to obtain the generalize eigenvalue problem and parametric studies are made to investigate the effect of aspect ratio, length-to-thickness ratio, number of layers, fibre orientation and material properties with respect to the frequency parameter. Some results are compared with the existing literature and other new results are given in tables and graphs.

Anti-beta2 glycoprotein 1 and the anti-phospholipid syndrome.

LENUS (Irish Health Repository)

Keane, Pearse A

2012-02-03

PURPOSE: To describe a patient who presented with bilateral retinal vascular occlusion and the use of anti-beta2 glycoprotein 1 (GPI) antibody testing in the diagnosis of antiphospholipid syndrome. DESIGN: Observational case report. METHODS: Hematological investigations were performed on a 49-year-old man who presented with rapid onset of bilateral severe central retinal vein occlusion. RESULTS: Lupus anticoagulant and anticardiolipin antibody testing was negative. Markedly raised titers of anti-beta2 GPI antibodies were detected on two separate occasions. CONCLUSIONS: The raised titers of anti-beta2 GPI antibodies were considered to strongly suggest an underlying diagnosis of the antiphospholipid syndrome.

Revealing the underlying drivers of disaster risk: a global analysis

Science.gov (United States)

Peduzzi, Pascal

2017-04-01

Disasters events are perfect examples of compound events. Disaster risk lies at the intersection of several independent components such as hazard, exposure and vulnerability. Understanding the weight of each component requires extensive standardisation. Here, I show how footprints of past disastrous events were generated using GIS modelling techniques and used for extracting population and economic exposures based on distribution models. Using past event losses, it was possible to identify and quantify a wide range of socio-politico-economic drivers associated with human vulnerability. The analysis was applied to about nine thousand individual past disastrous events covering earthquakes, floods and tropical cyclones. Using a multiple regression analysis on these individual events it was possible to quantify each risk component and assess how vulnerability is influenced by various hazard intensities. The results show that hazard intensity, exposure, poverty, governance as well as other underlying factors (e.g. remoteness) can explain the magnitude of past disasters. Analysis was also performed to highlight the role of future trends in population and climate change and how this may impacts exposure to tropical cyclones in the future. GIS models combined with statistical multiple regression analysis provided a powerful methodology to identify, quantify and model disaster risk taking into account its various components. The same methodology can be applied to various types of risk at local to global scale. This method was applied and developed for the Global Risk Analysis of the Global Assessment Report on Disaster Risk Reduction (GAR). It was first applied on mortality risk in GAR 2009 and GAR 2011. New models ranging from global assets exposure and global flood hazard models were also recently developed to improve the resolution of the risk analysis and applied through CAPRA software to provide probabilistic economic risk assessments such as Average Annual Losses (AAL

Análisis sentimental de la polaridad de tweets en tiempo real aplicando algoritmos de clasificación

OpenAIRE

Campillos García, Eduardo

2017-01-01

El objetivo de este proyecto es el análisis, desarrollo y evaluación de un sistema de clasificación de polaridad sobre un producto determinado a través del contenido generado en Twitter en español. En primer lugar, se ha estudiado la situación actual en el campo del análisis sentimental (AS) y los avances más notables en esta área perteneciente al procesamiento del lenguaje natural. En segundo lugar, una vez estudiado el estado del arte, se pasará a desarrollar el código que implementarem...

Linking national and global population agendas: case studies from eight developing countries.

Science.gov (United States)

Lee, K; Walt, G

1995-06-01

This comparative study of the determinants of family planning policy initiation and implementation focuses on four pairs of countries: Zambia/Zimbabwe, Algeria/Tunisia, Pakistan/Bangladesh, and Philippines/Thailand. The conclusion is drawn that global efforts had an influence on national policy makers and on putting family planning issues on the policy agenda. Global impacts were affected by national economic and social conditions and the broader political and economic relations with Western countries. The absolute level of economic development was found to be unrelated to the timing of initiation of family planning on national policy agendas. Stronger national family planning programs occurred in countries where policy makers linked economic development at whatever level with the need to limit population growth. Pakistan and Thailand in the 1960s illustrated this commitment to family planning programs, and Zambia and Algeria illustrated the lack of connection between development and population growth at the policy level and the lack of family planning on the policy agenda. Affiliation with the West during the 1960s meant early initiation of family planning in Pakistan/Bangladesh and Philippines/Thailand. Stronger commitment to program implementation occurred only in Thailand during the 1970s and Zimbabwe during the 1980s. Commitment lessened in the Philippines and Pakistan. Program implementation and national support of family planning were viewed as also dependent upon domestic factors, such as sufficient resources. Algeria/Tunisia and Zambia/Zimbabwe were countries that promoted family planning only after national political ideology shifted and anti-imperialist sentiments subsided. The impact of the international Cairo conference on these countries was minimal in terms of policy change. Most of the countries however desired greater support from donors. Even objections from the Vatican and internal domestic pressures were insufficient to prevent countries such as

Future aridity under conditions of global climate change

Science.gov (United States)

Asadi Zarch, Mohammad Amin; Sivakumar, Bellie; Malekinezhad, Hossein; Sharma, Ashish

2017-11-01

Global climate change is anticipated to cause some major changes in hydroclimatic conditions around the world. As aridity is a reliable indicator of potential available water, assessment of its changes under future climatic conditions is important for proper management of water. This study employs the UNESCO aridity/humidity index, which is a derivative of precipitation (P) and potential evapotranspiration (PET), for assessment of aridity. Historical (1901-2005) simulations and future (2006-2100) projections of 22 global climate models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are studied. The Nested Bias Correction (NBC) approach is used to correct possible biases of precipitation (simulated directly by the GCMs) and PET (estimated by applying FAO56-Penman-Monteith model on simulated parameters of the GCMs). To detect future aridity changes, the areal extents of the aridity zones in the past and future periods as well as through four sub-periods (2006-2025, 2026-2050, 2051-2075, and 2076-2100) of the future are compared. The results indicate that changes in climate will alter the areal extents of aridity zones in the future. In general, from the first sub-period towards the last one, the area covered by hyper-arid, arid, semi-arid, and sub-humid zones will increase (by 7.46%, 7.01%, 5.80%, and 2.78%, respectively), while the area of the humid regions will decrease (by 4.76%), suggesting that there will be less water over the global land area in the future. To understand the cause of these changes, precipitation and PET are also separately assumed to be stationary throughout the four future sub-periods and the resulting aridity changes are then analyzed. The results reveal that the aridity changes are mostly caused by the positive PET trends, even though the slight precipitation increase lessens the magnitude of the changes.

Apport de la théorie du sentiment d’autoefficacité pour le développement de la compétence technopédagogique des futurs enseignants

Directory of Open Access Journals (Sweden)

Sonia Lefebvre

2015-01-01

Full Text Available Le texte s’intéresse à la formation technopédagogique des futurs enseignants, et plus précisément, aux pratiques à déployer en formation initiale pour accroître leur compétence professionnelle à intégrer les TIC. Les pratiques proposées prennent appui sur la théorie du sentiment d’autoefficacité d’Albert Bandura, ce sentiment pouvant influencer leur compétence à intégrer les TIC. Appuyé par des travaux empiriques, le texte aborde les sources susceptibles d’influencer l’autoefficacité à intégrer les TIC dans un cadre pédagogique et identifie des pistes d’action à envisager. Enfin, la réflexion amène à repenser les interventions des formateurs tant en formation initiale qu’en formation continue et à remettre en question, sur le plan empirique, les dispositifs de formation.

An Agent-Based Model of School Closing in Under-Vacccinated Communities During Measles Outbreaks.

Science.gov (United States)

Getz, Wayne M; Carlson, Colin; Dougherty, Eric; Porco Francis, Travis C; Salter, Richard

2016-04-01

The winter 2014-15 measles outbreak in the US represents a significant crisis in the emergence of a functionally extirpated pathogen. Conclusively linking this outbreak to decreases in the measles/mumps/rubella (MMR) vaccination rate (driven by anti-vaccine sentiment) is critical to motivating MMR vaccination. We used the NOVA modeling platform to build a stochastic, spatially-structured, individual-based SEIR model of outbreaks, under the assumption that R 0 ≈ 7 for measles. We show this implies that herd immunity requires vaccination coverage of greater than approximately 85%. We used a network structured version of our NOVA model that involved two communities, one at the relatively low coverage of 85% coverage and one at the higher coverage of 95%, both of which had 400-student schools embedded, as well as students occasionally visiting superspreading sites (e.g. high-density theme parks, cinemas, etc.). These two vaccination coverage levels are within the range of values occurring across California counties. Transmission rates at schools and superspreading sites were arbitrarily set to respectively 5 and 15 times background community rates. Simulations of our model demonstrate that a 'send unvaccinated students home' policy in low coverage counties is extremely effective at shutting down outbreaks of measles.

Fake News and Indifference to Scientific Fact : President Trump's Confused Tweets on Global Warming, Climate Change and Weather

NARCIS (Netherlands)

D.E. Allen (David); M.J. McAleer (Michael)

2018-01-01

markdownabstractA set of 115 tweets on climate change by President Trump, from 2011 to 2015, are analysed by means of the data mining technique, sentiment analysis. The intention is to explore the contents and sentiments of the messages contained, the degree to which they differ, and their

Coupled fracture modes under anti-plane loading

Directory of Open Access Journals (Sweden)

Les P. Pook

2016-07-01

Full Text Available The linear elastic analysis of homogeneous, isotropic cracked bodies is a Twentieth Century development. It was recognised that the crack tip stress field is a singularity, but it was not until the introduction of the essentially two dimensional stress intensity factor concept in 1957 that widespread application to practical engineering problems became possible. The existence of three dimensional corner point effects in the vicinity of a corner point where a crack front intersects a free surface was investigated in the late 1970s: it was found that modes II and III cannot exist in isolation. The existence of one of these modes always induces the other. An approximate solution for corner point singularities by Bažant and Estenssoro explained some features of corner point effects but there were various paradoxes and inconsistencies. In an attempt to explain these a study was carried out on the coupled in-plane fracture mode induced by a nominal anti-plane (mode III loading applied to plates and discs weakened by a straight crack. The results derived from a large bulk of finite element models showed clearly that Bažant and Estenssoro’s analysis is incomplete. Some of the results of the study are summarised, together with some recent results for a disc under in-plane shear loading. On the basis of these results, and a mathematical argument, the results suggest that the stress field in the vicinity of a corner point is the sum of two singularities: one due to stress intensity factors and the other due to an as yet undetermined corner point singularity.

The challenge of market power under globalization

OpenAIRE

David Arie Mayer-Foulkes

2014-01-01

The legacy of Adam Smith leads to a false confidence on the optimality of laissez faire policies for the global market economy. Instead, the polarized character of current globalization deeply affects both developed and underdeveloped economies. Current globalization is characterized by factor exchange between economies of persistently unequal development. This implies the existence of persistent extraordinary market power in transnational corporations, reflected in their disproportionate par...

Impacts of climate extremes on gross primary production under global warming

International Nuclear Information System (INIS)

Williams, I N; Torn, M S; Riley, W J; Wehner, M F

2014-01-01

The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at the warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate projections

Predicting the probability of recession in Croatia:Is economic sentiment the missing link?

Directory of Open Access Journals (Sweden)

Nataša Erjavec

2016-12-01

Full Text Available This paper aims to assess the possibility of predicting Croatian recessionary episodes using probit models. The authors first estimate a baseline static model using four leading indicators of recession (monetary base, unemployment, industrial production, and CROBEX stock market index. Lag lengths of up to 6 months are examined for each of the observed variables in the probit specification, and several important conclusions arise from the estimated models. First, the stock market and money supply exhibit the most pronounced leading characteristics in the Croatian economy (a 3-month lag length is selected by the information criteria. Second, the dynamic model (including a lagged dependent dummy variable significantly outperforms the baseline static model. Third, the authors augment the probit model by the Economic Sentiment Indicator, which significantly contributes to the model accuracy. The latter confirms the main hypothesis of the paper, going in line with the assertion that psychological factors largely govern the economic cycles, growing in significance in times of economic hardship.

Style of management and chosen sentiments and attitudes among employees of scientific organizations

Directory of Open Access Journals (Sweden)

Agnieszka Izabela Baruk

2015-06-01

Full Text Available The article presents issues associated with the style of management applied in scientific organizations in the context of sentiments and attitudes of employees. Attention is drawn particularly to the relations between the style of management perceived by employees and the level of their perceived contentedness and the perceived level of satisfaction, as well as between the perceived style of management and attitude reflecting their readiness to recommend an organization as an employer. The application of the method of statistical analysis, namely, the analysis of correspondence allowed drawing the conclusion that there are statistically important relations between the variables. These relations are comparably strongest in case of the perceived style of management and the level of satisfaction. Thus, it can be concluded that applying democratic style to employees favours stimulating their satisfaction and contentedness and at the same time contributes to assuming an open attitude characterized by the readiness to recommend an organization as a workplace and thus co-create its positive image.

Democratization and Political Change as Threats to Collective Sentiments: Testing Durkheim in Russia.

Science.gov (United States)

Pridemore, William Alex; Kim, Sang-Weon

2006-05-01

Durkheim argued that acute political crises result in increased homicide rates because they pose a threat to sentiments about the collective. Though crucial to Durkheim's work on homicide, this idea remains untested. The authors took advantage of the natural experiment of the collapse of the Soviet Union to examine this hypothesis. Using data from Russian regions (N = 78) and controlling for measures of anomie and other covariates, the authors estimated the association between political change and change in homicide rates between 1991 and 2000. Results indicated that regions exhibiting less support for the Communist Party in 2000 (and thus greater change in political ideals because the Party had previously exercised complete control) were regions with greater increases in homicide rates. Thus, while democratization may be a positive development relative to the Communist juggernaut of the past, it appears that the swift political change in Russia is partially responsible for the higher rates of violence there following the collapse of the Soviet Union.

Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

Energy Technology Data Exchange (ETDEWEB)

Cook, Kerry H. [Univ. of Texas, Austin, TX (United States); Vizy, Edward [Univ. of Texas, Austin, TX (United States)

2016-02-08

The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understanding of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.

Projected global ground-level ozone impacts on vegetation under different emission and climate scenarios

Directory of Open Access Journals (Sweden)

P. Sicard

2017-10-01

Full Text Available The impact of ground-level ozone (O3 on vegetation is largely under-investigated at the global scale despite large areas worldwide that are exposed to high surface O3 levels. To explore future potential impacts of O3 on vegetation, we compared historical and projected surface O3 concentrations simulated by six global atmospheric chemistry transport models on the basis of three representative concentration pathways emission scenarios (i.e. RCP2.6, 4.5, 8.5. To assess changes in the potential surface O3 threat to vegetation at the global scale, we used the AOT40 metric. Results point out a significant exceedance of AOT40 in comparison with the recommendations of UNECE for the protection of vegetation. In fact, many areas of the Northern Hemisphere show that AOT40-based critical levels will be exceeded by a factor of at least 10 under RCP8.5. Changes in surface O3 by 2100 worldwide range from about +4–5 ppb in the RCP8.5 scenario to reductions of about 2–10 ppb in the most optimistic scenario, RCP2.6. The risk of O3 injury for vegetation, through the potential O3 impact on photosynthetic assimilation, decreased by 61 and 47 % under RCP2.6 and RCP4.5, respectively, and increased by 70 % under RCP8.5. Key biodiversity areas in southern and northern Asia, central Africa and North America were identified as being at risk from high O3 concentrations.

Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network

Science.gov (United States)

Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor

2012-01-01

High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a

Understanding the bubbles

DEFF Research Database (Denmark)

Turcan, Romeo V.

that are identified to exist between the Internet and housing market bubbles: uncertainty and sentiments. The iteration between uncertainty and sentiments leads to the emergence of the third commonality: residue. The residue is the difference between the actors’ overall sentiment about exaggerated future prospects...... all boils down to the role pricing plays vis-à-vis the emergence of a new venture and its perceived value. Being in the midst of the global economic crisis provides us with a unique opportunity to refine the proposed model, especially by understanding its temporal and contextual boundaries....

Basket weaving and social weaving

DEFF Research Database (Denmark)

Olwig, Mette Fog; Gough, Katherine

2013-01-01

An important topic in climate change discourse is the question of ``climate refugees'' and climate-related mobility, which is often presented as failed adaptation. This discourse feeds into, and reinvigorates, anti-mobility sentiments, especially concerning youth, among nongovernmental...... and governmental organizations that conceptualize mobility as involuntary and associated with social rupture. Challenging this understanding, we argue that mobility can be an important strategy for mobilizing resources through social relations, what we call ``social weaving.'' Analyzing young northern Ghanaian...... demonstrate how the development field can be seen to be largely based on, as well as generating, social relations. Indeed, while there has been a tendency towards anti-mobility sentiments among development organizations, NGOs themselves often become woven into the local artisans' fabric of relations...

Nitrogen leaching from natural ecosystems under global change: a modelling study

Science.gov (United States)

Braakhekke, Maarten C.; Rebel, Karin T.; Dekker, Stefan C.; Smith, Benjamin; Beusen, Arthur H. W.; Wassen, Martin J.

2017-12-01

To study global nitrogen (N) leaching from natural ecosystems under changing N deposition, climate, and atmospheric CO2, we performed a factorial model experiment for the period 1901-2006 with the N-enabled global terrestrial ecosystem model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator). In eight global simulations, we used either the true transient time series of N deposition, climate, and atmospheric CO2 as input or kept combinations of these drivers constant at initial values. The results show that N deposition is globally the strongest driver of simulated N leaching, individually causing an increase of 88 % by 1997-2006 relative to pre-industrial conditions. Climate change led globally to a 31 % increase in N leaching, but the size and direction of change varied among global regions: leaching generally increased in regions with high soil organic carbon storage and high initial N status, and decreased in regions with a positive trend in vegetation productivity or decreasing precipitation. Rising atmospheric CO2 generally caused decreased N leaching (33 % globally), with strongest effects in regions with high productivity and N availability. All drivers combined resulted in a rise of N leaching by 73 % with strongest increases in Europe, eastern North America and South-East Asia, where N deposition rates are highest. Decreases in N leaching were predicted for the Amazon and northern India. We further found that N loss by fire regionally is a large term in the N budget, associated with lower N leaching, particularly in semi-arid biomes. Predicted global N leaching from natural lands rose from 13.6 Tg N yr-1 in 1901-1911 to 18.5 Tg N yr-1 in 1997-2006, accounting for reductions of natural land cover. Ecosystem N status (quantified as the reduction of vegetation productivity due to N limitation) shows a similar positive temporal trend but large spatial variability. Interestingly, this variability is more strongly related to vegetation type than N input

Prerequisites for Forming the Institutional Concept of the National Economy Competitiveness under Conditions of Globalization

Directory of Open Access Journals (Sweden)

Yaremenko Oleh L.

2015-03-01

Full Text Available The article attempts to prove that under conditions of globalization there have developed objective and subjective prerequisites for forming the institutional concept of the national economy. The objective prerequisites are the newest information and communication technologies, post-industrial trends and market transformation of civilization intensified by globalization. Under such conditions instability and volatility of the institutional environment both within national economies and at the international level are observed. The aggravation of the global competition between national economies actualizes the role of such institutional factors as political system, property, public administration, economic organization, culture, etc. The subjective prerequisites are related to the fact that the institutional economic theory is currently one of the leading trends in the modern world and Ukrainian economic thought. Interest in it is explained not only by the fact that it overcomes the limitations of a number of prerequisites for the mainstream, but also because it allows considering the modern economic processes in complex

Twitter and traumatic brain injury: A content and sentiment analysis of tweets pertaining to sport-related brain injury.

Science.gov (United States)

Workewych, Adriana M; Ciuffetelli Muzzi, Madeline; Jing, Rowan; Zhang, Stanley; Topolovec-Vranic, Jane; Cusimano, Michael D

2017-01-01

Sport-related traumatic brain injuries are a significant public health burden, with hundreds of thousands sustained annually in North America. While sports offer numerous physical and social health benefits, traumatic brain injuries such as concussion can seriously impact a player's life, athletic career, and sport enjoyment. The culture in many sports encourages winning at all costs, placing athletes at risk for traumatic brain injuries. As social media has become a central part of everyday life, the content of users' messages often reflects the prevailing culture related to a particular event or health issue. We hypothesized that Twitter data might be useful for understanding public perceptions and misperceptions of sport-related traumatic brain injuries. We performed a content and sentiment analysis of 7483 Twitter ® tweets related to traumatic brain injuries in sports collected during June and July 2013. We identified five major themes. Users tweeted about personal traumatic brain injuries experiences, reported traumatic brain injuries in professional athletes, shared research about sport-related concussions, and discussed policy and safety in injury prevention, such as helmet use. We identified mixed perceptions of and sentiment toward traumatic brain injuries in sports: both an understanding that brain injuries are serious and disregard for activities that might reduce the public burden of traumatic brain injuries were prevalent in our Twitter analysis. While the scientific and medical community considers a concussion a form of traumatic brain injuries, our study demonstrates a misunderstanding of this fact among the public. In our current digital age, social media can provide useful insight into the culture around a health issue, facilitating implementation of prevention and treatment strategies.

Evaluation of the effect of processing methods on the nutritional and anti-nutritional compositions of two under-utilized Nigerian grain legumes.

Science.gov (United States)

Oke, M O; Sobowale, S S; Ogunlakin, G O

2013-12-15

The nutritional and anti-nutritional compositions of African Yam Bean (AYB) and Lima bean flours under different processing methods were determined. Nutritional and anti-nutritional properties studied include moisture content, crude protein, crude fibre, ash content, ether extract, carbohydrate, tannin, protease inhibitor and phytate. The moisture content of AYB flours ranged from 9.31 to 9.61% while that of lima beans ranged from 9.32 to 9.56%. There is a significant different among the samples when the unprocessed AYB (control) and the processed AYB were compared. The same trend was also observed with lima bean flours. However, some nutrient did not show significant variations with processing. It was observed that samples of soaked/de-hulled AYB have the least protease inhibitor of 0.73 mg/100 g and it is significantly different from the unprocessed samples. Soaked/de-hulled flours of both AYB and lima beans have the most percentage decrease in anti-nutritional content. Lima bean flours were observed to have higher anti-nutritional content than AYB. The percentage decrease of anti-nutritional factors in the samples is proportionally higher than that of the nutrients. The nutritional and anti-nutritional compositions of the samples suggest that processed African Yam Bean (AYB) and Lima bean flours would have useful application in fabricated foods.

Naive Bayes as opinion classifier to evaluate students satisfaction based on student sentiment in Twitter Social Media

Science.gov (United States)

Candra Permana, Fahmi; Rosmansyah, Yusep; Setiawan Abdullah, Atje

2017-10-01

Students activity on social media can provide implicit knowledge and new perspectives for an educational system. Sentiment analysis is a part of text mining that can help to analyze and classify the opinion data. This research uses text mining and naive Bayes method as opinion classifier, to be used as an alternative methods in the process of evaluating studentss satisfaction for educational institution. Based on test results, this system can determine the opinion classification in Bahasa Indonesia using naive Bayes as opinion classifier with accuracy level of 84% correct, and the comparison between the existing system and the proposed system to evaluate students satisfaction in learning process, there is only a difference of 16.49%.

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning.

Science.gov (United States)

Cole-Lewis, Heather; Varghese, Arun; Sanders, Amy; Schwarz, Mary; Pugatch, Jillian; Augustson, Erik

2015-08-25

Electronic cigarettes (e-cigarettes) continue to be a growing topic among social media users, especially on Twitter. The ability to analyze conversations about e-cigarettes in real-time can provide important insight into trends in the public's knowledge, attitudes, and beliefs surrounding e-cigarettes, and subsequently guide public health interventions. Our aim was to establish a supervised machine learning algorithm to build predictive classification models that assess Twitter data for a range of factors related to e-cigarettes. Manual content analysis was conducted for 17,098 tweets. These tweets were coded for five categories: e-cigarette relevance, sentiment, user description, genre, and theme. Machine learning classification models were then built for each of these five categories, and word groupings (n-grams) were used to define the feature space for each classifier. Predictive performance scores for classification models indicated that the models correctly labeled the tweets with the appropriate variables between 68.40% and 99.34% of the time, and the percentage of maximum possible improvement over a random baseline that was achieved by the classification models ranged from 41.59% to 80.62%. Classifiers with the highest performance scores that also achieved the highest percentage of the maximum possible improvement over a random baseline were Policy/Government (performance: 0.94; % improvement: 80.62%), Relevance (performance: 0.94; % improvement: 75.26%), Ad or Promotion (performance: 0.89; % improvement: 72.69%), and Marketing (performance: 0.91; % improvement: 72.56%). The most appropriate word-grouping unit (n-gram) was 1 for the majority of classifiers. Performance continued to marginally increase with the size of the training dataset of manually annotated data, but eventually leveled off. Even at low dataset sizes of 4000 observations, performance characteristics were fairly sound. Social media outlets like Twitter can uncover real-time snapshots of

Anti-HCV activity of the Chinese medicinal fungus Cordyceps militaris.

Science.gov (United States)

Ueda, Youki; Mori, Kyoko; Satoh, Shinya; Dansako, Hiromichi; Ikeda, Masanori; Kato, Nobuyuki

2014-05-02

Persistent hepatitis C virus (HCV) infection causes chronic liver diseases and is a global health problem. Although the sustained virologic response rate in the treatment of genotype 1 using new triple therapy (pegylated-interferon, ribavirin, and telaprevir/boceprevir) has been improved by more than 70%, several severe side effects such as skin rash/ageusia and advanced anemia have become a problem. Under these circumstances, a new type of anti-HCV oral drug with few side effects is needed. Our recently developed HCV drug assay systems, including the HuH-7 cell line-derived OR6 and AH1R, and the Li23 cell line-derived ORL8 and ORL11, allow genome-length HCV RNAs (several strains of genotype 1b) encoding renilla luciferase to replicate efficiently. Using these systems as anti-HCV candidates, we have identified numerous existing medicines that can be used against HCV with few side effects, such as statins and teprenon. To obtain additional anti-HCV candidates, we evaluated a number of oral health supplements, and found that the capsule but not the liquid form of Cordyceps militaris (CM) (Ascomycotinanorth, North Chinese caterpillar fungus), which is used as a Chinese herbal medicine, exhibited moderate anti-HCV activity. In combination with interferon-α or ribavirin, CM exhibited an additive inhibitory effect. Among the main components of CM, cordycepin, but not ergosterol, contributed to the anti-HCV activity of CM. In consideration of all these results, we suggest that CM would be useful as an oral anti-HCV agent in combination with interferon-α and/or ribavirin. Copyright © 2014 Elsevier Inc. All rights reserved.

Logistics Concepts at the Industrial Enterprise under Conditions of the Globalization of Markets

Directory of Open Access Journals (Sweden)

Trushkina Nataliia V.

2016-08-01

Full Text Available The aim of the article is to assess the dynamics of indicators of Ukraine’s foreign trade in goods and services; conduct a comparative analysis of logistics concepts used at industrial enterprises under conditions of the globalization of markets; determine the ways to improve the management of international production and distribution activities of industrial enterprises. The study analyzes the dynamics of volumes of exports–imports of goods and transport services in Ukraine; freight traffic by mode of transport; export, import and transit of goods; foreign direct investment from countries of the world in the Ukrainian economy. Modern information systems and logistics concepts used at industrial enterprises under conditions of the globalization of markets are considered. The ways to improve the management of international production and distribution activities of industrial enterprises are defined and systematized. Prospects for further research in this direction are the development of proposals for information support of providing services for customers of the industrial enterprise.

THE NONLINEAR IMPACT OF GLOBALIZATION ON CORRUPTION

OpenAIRE

Jayoti Das; Cassandra DiRienzo

2009-01-01

Some researchers have argued that globalization has increased the opportunity for corrupt practices, while others state that globalization has lead to a decrease in corruption as countries wishing to join the global economy must comply with international anti-corruption rules and regulations. This study empirically explores this paradox using the Corruption Perceptions Index (CPI) and the Konjunkturforschungsstelle (KOF) globalization Index. The results suggest that a nonlinear relationship e...

ECONOMIC NATIONALISM’S VIABILITY UNDER GLOBALIZATION

Directory of Open Access Journals (Sweden)

Elena Mihaela ILIESCU

2015-07-01

Full Text Available The path undertaken by the world economy is irreversible - the world economic system is a system based on interdependencies, cooperation and multilateralism but economic openness is not full. Each country, in order to protect their national interest call, in different proportion, depending on the circumstances and of the economic-social and political interests, for different forms of the economic nationalism, forms that have adapted continuously to the demands required for integrating on the foreign markets. The recent global economic crisis intensified the rhetoric and the economic nationalism’s practices but it is not about rebirth, but of renewal, of remodeling the nationalist policies, globalization being a premise of the new economic nationalism. The scope of this paper is to emphasize using empirical data the fact that nationalism and globalization, from an economical point of view, are not antagonistic policies, they coexist and influence each other, both generating contradictory effects, in terms of provided opportunities and risks.

Three-dimensional effects on cracked components under anti-plane loading

Directory of Open Access Journals (Sweden)

F. Berto

2015-07-01

Full Text Available The existence of three-dimensional effects at cracks has been known for many years, but understanding has been limited, and for some situations still is. Understanding improved when the existence of corner point singularities and their implications became known. Increasingly powerful computers made it possible to investigate three-dimensional effects numerically in detail. Despite increased understanding, threedimensional effects are sometimes ignored in situations where they may be important. The purpose of the present investigation is to study by means of accurate 3D finite element (FE models a coupled fracture mode generated by anti-plane loading of a straight through-the-thickness crack in linear elastic plates. An extended version of the present work has recently been published in the literature. The results obtained from the highly accurate finite element analyses have improved understanding of the behaviour of through cracked components under anti-plane loading. The influence of plate bending is increasingly important as the thickness decreases. It appears that a new field parameter, probably a singularity, is needed to describe the stresses at the free surfaces. Discussion on whether KIII tends to zero or infinity as a corner point is approached is futile because KIII is meaningless at a corner point. The intensity of the local stress and strain state through the thickness of the cracked components has been evaluated by using the strain energy density (SED averaged over a control volume embracing the crack tip. The SED has been considered as a parameter able to control fracture in some previous contributions and can easily take into account also coupled three-dimensional effects. Calculation of the SED shows that the position of the maximum SED is independent of plate thickness. Both for thin plates and for thick ones the maximum SED is close to the lateral surface, where the maximum intensity of the coupled mode II takes place.

Facial expression recognition under partial occlusion based on fusion of global and local features

Science.gov (United States)

Wang, Xiaohua; Xia, Chen; Hu, Min; Ren, Fuji

2018-04-01

Facial expression recognition under partial occlusion is a challenging research. This paper proposes a novel framework for facial expression recognition under occlusion by fusing the global and local features. In global aspect, first, information entropy are employed to locate the occluded region. Second, principal Component Analysis (PCA) method is adopted to reconstruct the occlusion region of image. After that, a replace strategy is applied to reconstruct image by replacing the occluded region with the corresponding region of the best matched image in training set, Pyramid Weber Local Descriptor (PWLD) feature is then extracted. At last, the outputs of SVM are fitted to the probabilities of the target class by using sigmoid function. For the local aspect, an overlapping block-based method is adopted to extract WLD features, and each block is weighted adaptively by information entropy, Chi-square distance and similar block summation methods are then applied to obtain the probabilities which emotion belongs to. Finally, fusion at the decision level is employed for the data fusion of the global and local features based on Dempster-Shafer theory of evidence. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the effectiveness and fault tolerance of this method.

Democracy under siege: Democratic solidarity between global crisis and cosmopolitan hope

Directory of Open Access Journals (Sweden)

Brunkhorst Hauke

2017-01-01

Full Text Available For almost half a century (between 1940 and 1990 the democratic and social state has solved the twofold problem of growth and social exclusion through social inclusion within the borders of the national state. This solution since the 1970s came under threat of multiple crises of the environment, secular stagnation, under-consumption, legitimization and constitutionalization. There might be a social solution of present crisis possible through massive redistribution plus decent basic income (on the level of tuition-costs plus green growth. However, after globalization of capital there are no longer national social alternatives available. Therefore, there is no alternative to transnational democratic state-formation. But are there actors relevant, strong and motivated enough to do that?

Islamic and conventional bank market value: Manager behavior and investor sentiment

Directory of Open Access Journals (Sweden)

Mouna Abdelhedi-Zouch

2016-12-01

Full Text Available This paper studies the effect of bank manager behavior and investor behavior on market value of Islamic and conventional banks in the Middle East and North Africa region. Firstly, our analysis denoted the positive effect of discretionary behavior of manager on both types of banks on share prices since discretionary behavior transmits to investor a positive signal of future earnings’ prospects. Also, we find that the conventional bank stock prices response is very high to negative signal compared with positive signal. This result is explained by prospect theory and loss aversion bias which specified that individuals are more sensitive to losses than gains of same magnitude. In particular, we discover that the negative effect of non-discretionary behavior is much lower on Islamic bank value since investors give more confidence to Islamic bank because they are motivated by the idea that Islamic banks are safer than conventional banks. Secondly, the results show that investor sentiment affects significantly both bank market prices. Thus, both Islamic and conventional banks’ market value depends similarly on manager and investor behavior. The implication of this paper is that Islamic bank concentrations reveal a positive effect on their price values because of the recently increased investments in Islamic banks.

The anti-aging and anti-oxidation effects of tea water extract in Caenorhabditis elegans.

Science.gov (United States)

Fei, Tianyi; Fei, Jian; Huang, Fang; Xie, Tianpei; Xu, Jifeng; Zhou, Yi; Yang, Ping

2017-10-15

Tea includes puer tea, black tea, green tea and many others. By using model organism Caenorhabditis elegans, the anti-aging and anti-oxidation effects of tea water extract were systemically examined in this study. We found that water extract of puer tea, black tea and green tea all increased the lifespan of worms, postponed Aβ-induced progressive paralysis in Alzheimer's disease transgenic worms, and improved the tolerance of worms to the oxidative stress induced by heavy metal Cr 6+ . Moreover, the anti-oxidation effects of tea water extract at low concentration were different among 4 kinds of brands of green tea. The underlying mechanisms were further explored using genetically manipulated-mutant worms. The anti-oxidative stress effects of green tea water extract depend on the dietary restriction and germline signaling pathways, but not the FOXO and mitochondrial respiratory chain signals. Therefore, tea water extract provides benefits of anti-aging, anti-AD and anti-oxidation. Copyright © 2017. Published by Elsevier Inc.

Anti-gay sentiment among adolescents in Belgium and Canada: a comparative investigation into the role of gender and religion.

Science.gov (United States)

Hooghe, Marc; Claes, Ellen; Harell, Allison; Quintelier, Ellen; Dejaeghere, Yves

2010-01-01

Previous research has indicated that opposition toward lesbian, gay, bisexual, and trangender (LGBT) rights remains prevalent among Western populations. In this article, we investigate the determinants of anti-gay attitudes among adolescents in two liberal democracies, Belgium (n = 6,330) and Canada (n = 3,334). The analysis indicates that hostile feelings toward LGBT rights are particularly widespread among boys, while the effects of socioeconomic status and parental education remain limited. Various religious denominations proved to have a strong and significant negative impact on tolerance, with especially high scores for Islam. Religious practice, too, contributes to a negative attitude toward LGBT rights. The consequences of these findings with regard to tolerance for gay rights among Islamic youth in Western democracies are discussed.

Dynamics in non-globally-hyperbolic static spacetimes: III. Anti-de Sitter spacetime

International Nuclear Information System (INIS)

Ishibashi, Akihiro; Wald, Robert M

2004-01-01

In recent years, there has been considerable interest in theories formulated in anti-de Sitter (AdS) spacetime. However, AdS spacetime fails to be globally hyperbolic, so a classical field satisfying a hyperbolic wave equation on AdS spacetime need not have a well-defined dynamics. Nevertheless, AdS spacetime is static, so the possible rules of dynamics for a field satisfying a linear wave equation are constrained by our previous general analysis-given in paper II-where it was shown that the possible choices of dynamics correspond to choices of positive, self-adjoint extensions of a certain differential operator, A. In the present paper, we reduce the analysis of electromagnetic and gravitational perturbations in AdS spacetime to scalar wave equations. We then apply our general results to analyse the possible dynamics of scalar, electromagnetic and gravitational perturbations in AdS spacetime. In AdS spacetime, the freedom (if any) in choosing self-adjoint extensions of A corresponds to the freedom (if any) in choosing suitable boundary conditions at infinity, so our analysis determines all the possible boundary conditions that can be imposed at infinity. In particular, we show that other boundary conditions besides the Dirichlet and Neumann conditions may be possible, depending on the value of the effective mass for scalar field perturbations, and depending on the number of spacetime dimensions and type of mode for electromagnetic and gravitational perturbations

Enhanced or Weakened Western North Pacific Subtropical High under Global Warming?

OpenAIRE

He, Chao; Zhou, Tianjun; Lin, Ailan; Wu, Bo; Gu, Dejun; Li, Chunhui; Zheng, Bin

2015-01-01

The Western North Pacific Subtropical High (WNPSH) regulates East Asian climate in summer. Anomalous WNPSH causes floods, droughts and heat waves in China, Japan and Korea. The potential change of the WNPSH under global warming is concerned by Asian people, but whether the WNPSH would be enhanced or weakened remains inconclusive. Based on the multi-model climate change projection from the 5th phase of Coupled Model Intercomparison Project (CMIP5), we show evidences that the WNPSH tends to wea...

Research on optimal investment path of transmission corridor under the global energy Internet

Science.gov (United States)

Huang, Yuehui; Li, Pai; Wang, Qi; Liu, Jichun; Gao, Han

2018-02-01

Under the background of the global energy Internet, the investment planning of transmission corridor from XinJiang to Germany is studied in this article, which passes through four countries: Kazakhstan, Russia, Belarus and Poland. Taking the specific situation of different countries into account, including the length of transmission line, unit construction cost, completion time, transmission price, state tariff, inflation rate and so on, this paper constructed a power transmission investment model. Finally, the dynamic programming method is used to simulate the example, and the optimal strategies under different objective functions are obtained.

Current Status of Doping in Japan Based on Japan Anti-Doping Disciplinary Panels of the Japan Anti-Doping Agency (JADA): A Suggestion on Anti-Doping Activities by Pharmacists in Japan.

Science.gov (United States)

Imanishi, Takashi; Kawabata, Takayoshi; Takayama, Akira

2017-01-01

In 2009, the Japan Anti-Doping Agency (JADA) established the "Sports Pharmacist Accreditation Program" to prevent doping in sports. Since then, anti-doping activities in Japan have been attracting attention. In this study, we investigated research about the current status of doping from 2007 to 2014 in Japan to make anti-doping activities more concrete, and we also discussed future anti-doping activities by pharmacists. In Japan, bodybuilding was the sporting event with the highest number and rate of doping from 2007 to 2014. Many of the positive doping cases were detected for class S1 (anabolic agents), S5 (diuretics and masking agents), and S6 (stimulants). Within class S1, supplements were the main cause of positive doping. Within class S5, medicines prescribed by medical doctors were the main cause of positive doping. Within class S6, non-prescription medicines (e.g., OTC) were the main cause of positive doping. When we looked at the global statistics on doping, many of the positive doping cases were detected for class S1. On comparing the Japanese statistics with the global statistics, the rate of positive doping caused by class S1 was significantly lower, but that caused by classes S5 and S6 was significantly higher in Japan than in the world. In conclusion, pharmacists in Japan should pay attention to class S1, S5, and S6 prohibited substances and to the sport events of bodybuilding. Based on this study, sports pharmacists as well as common pharmacists should suggest new anti-doping activities to prevent doping in the future.

Transformation of India's transport sector under Global Warming of 2oC and 1.5oC Scenario

DEFF Research Database (Denmark)

Dhar, Subash; Pathak, Minal; Shukla, P.R.

2018-01-01

The Paris agreement stresses on concerted efforts to limit global temperature increase to 2°C and make efforts towards achieving 1.5°C temperature stabilization. Countries announced actions under the Nationally Determined Contributions outlining domestic mitigation actions to achieve the global...

Impacts of the Tropical Pacific Cold Tongue Mode on ENSO Diversity Under Global Warming

Science.gov (United States)

Li, Yang; Li, Jianping; Zhang, Wenjun; Chen, Quanliang; Feng, Juan; Zheng, Fei; Wang, Wei; Zhou, Xin

2017-11-01

The causes of ENSO diversity, although being of great interest in recent research, do not have a consistent explanation. This study provides a possible mechanism focused on the background change of the tropical Pacific as a response to global warming. The second empirical orthogonal function mode of the sea surface temperature anomalies (SSTA) in the tropical Pacific, namely the cold tongue mode (CTM), represents the background change of the tropical Pacific under global warming. Using composite analysis with surface observations and subsurface ocean assimilation data sets, we find ENSO spatial structure diversity is closely associated with the CTM. A positive CTM tends to cool the SST in the eastern equatorial Pacific and warm the SST outside, as well as widen (narrow) zonal and meridional scales for El Niño (La Niña), and vice versa. Particularly in the positive CTM phase, the air-sea action center of El Niño moves west, resembling the spatial pattern of CP-El Niño. This westward shift of center is related to the weakened Bjerknes feedback (BF) intensity by the CTM. By suppressing the SSTA growth of El Niño in the eastern equatorial Pacific, the CTM contributes to more frequent occurrence of CP-El Niño under global warming.

Ce “sentiment de culpabilité” That “Guilty Feeling” : Emotions and Motivation in Migration and Transnational Caregiving’

Directory of Open Access Journals (Sweden)

Loretta Baldassar

2010-10-01

Full Text Available Cet article explore l’expérience de la “culpabilité” en tant qu’émotion jouant un rôle moteur dans les obligations réciproques de soin dans les relations familiales transnationales. Je pose l’hypothèse qu’en créant une séparation physique, une absence et un sentiment de manque, l’acte migratoire pousse les migrants à se sentir coupables de ne pas remplir l’obligation morale de coprésence. Les migrants se sentent souvent coupables de ne pas être présents pour s’occuper de leurs parents âgés ; les parents se sentent souvent coupables de ne pas participer à la vie de leurs enfants et de leurs petits-enfants. Ce “sentiment de culpabilité” les encourage à “rester en contact” aussi souvent et effectivement que possible en créant des occasions leur permettant d’échanger coprésence et don de soi. En renforçant les relations, en exerçant une influence sur autrui, et en allégeant les inégalités relationnelles, la culpabilité peut servir au final à renforcer et maintenir les relations de soin transnationales. Cependant, dans les relations transnationales où les devoirs sont trop lourds pour être remplis, les individus peuvent se désengager du soin afin d’éviter des sentiments de culpabilité accablants et fragilisants.This paper explores the experience of “guilt” as a motivating emotion in reciprocal obligations to care in transnational kinship relations. My hypothesis is that the act of migration, by causing physical separation, absence and longing, causes migrants to feel guilty about their moral obligations to be co-present. For instance, migrants often feel guilty about not being present to look after ageing parents; similarly, parents often feel guilty about not participating in the lives of their children and especially grandchildren. This “guilty feeling” motivates them to “stay in touch” as often and as effectively as they can by creating opportunities in which they can

The global anti-phospholipid syndrome score in primary APS.

Science.gov (United States)

Sciascia, Savino; Sanna, Giovanni; Murru, Veronica; Roccatello, Dario; Khamashta, Munther A; Bertolaccini, Maria Laura

2015-01-01

The aim of this study was to evaluate the clinical relevance of the global APS score (GAPSS) in a cohort of primary APS patients. This study included 62 consecutive patients with primary APS. Data on clinical manifestations, conventional cardiovascular risk factors and aPL profile were collected. The GAPSS was calculated for each patient by adding together the points corresponding to the risk factors, based on a linear transformation derived from the β regression coefficient as follows: 3 for hyperlipidaemia, 1 for arterial hypertension, 5 for aCL IgG/IgM, 4 for anti-β2 glycoprotein I IgG/IgM, 3 for aPS-PT IgG/IgM and 4 for LA. Higher GAPSS values were seen in patients who experienced thrombosis alone when compared with those with pregnancy loss alone [11.5 (S.D. 4.6) and 8.7 (S.D. 3.2), P = 0.04]. Patients with both thrombosis and pregnancy loss showed higher GAPSS than those with pregnancy loss alone [12.5 (S.D. 4.6) vs 8.7 (S.D. 3.2), P = 0.02]. Higher GAPSS values were also shown after subgrouping for the site of thrombosis when compared with pregnancy loss alone [12.2 (S.D. 5.2) for arterial thrombosis, 12.0 (S.D. 4.0) for venous vs 8.7 (S.D. 3.2), P = 0.02 and P = 0.04, respectively]. Patients with thrombotic recurrences showed higher GAPSS values when compared with those without recurrence [13.7 (S.D. 3.1) vs 9.4 (S.D. 3.9), P = 0.02]. This was also seen when comparing recurrences vs no recurrences independently of the site of the thrombotic event [13.9 (S.D. 3.6) vs 11.0 (S.D. 4.3), P = 0.01 for arterial and 13.6 (S.D. 2.18) vs 8.91 (S.D. 3.6), P APS. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Inequality and anti-globalization backlash by political parties

NARCIS (Netherlands)

Burgoon, B.

2013-01-01

Does income inequality increase political backlash against European and global integration? This paper reports research suggesting that it can. The article analyses party opposition to and support for trade openness, European Union integration and general internationalism of political party

Solidarity, authenticity and anti racism

Directory of Open Access Journals (Sweden)

Dinesh Wadiwel

2009-08-01

Full Text Available Anti Racist struggles often aim to construct alliances between groups under the banner of "solidarity" in order to achieve change. Using Foucault's Society Must be Defended lectures as a basis, this paper interrogates the difficulties associated with creating solidarity in anti racist movements, when conflict and war might be treated as the basis for racial stratifications. Following from this, it is argued that friendships in spite of differences are possible under the guise of "truce": that is through allegiances that begin by acknowledging the fact of war.

Tracking the global maximum power point of PV arrays under partial shading conditions

Science.gov (United States)

Fennich, Meryem

This thesis presents the theoretical and simulation studies of the global maximum power point tracking (MPPT) for photovoltaic systems under partial shading. The main goal is to track the maximum power point of the photovoltaic module so that the maximum possible power can be extracted from the photovoltaic panels. When several panels are connected in series with some of them shaded partially either due to clouds or shadows from neighboring buildings, several local maxima appear in the power vs. voltage curve. A power increment based MPPT algorithm is effective in identifying the global maximum from the several local maxima. Several existing MPPT algorithms are explored and the state-of-the-art power increment method is simulated and tested for various partial shading conditions. The current-voltage and power-voltage characteristics of the PV model are studied under different partial shading conditions, along with five different cases demonstrating how the MPPT algorithm performs when shading switches from one state to another. Each case is supplemented with simulation results. The method of tracking the Global MPP is based on controlling the DC-DC converter connected to the output of the PV array. A complete system simulation including the PV array, the direct current to direct current (DC-DC) converter and the MPPT is presented and tested using MATLAB software. The simulation results show that the MPPT algorithm works very well with the buck converter, while the boost converter needs further changes and implementation.

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning

Science.gov (United States)

Cole-Lewis, Heather; Varghese, Arun; Sanders, Amy; Schwarz, Mary; Pugatch, Jillian

2015-01-01

Background Electronic cigarettes (e-cigarettes) continue to be a growing topic among social media users, especially on Twitter. The ability to analyze conversations about e-cigarettes in real-time can provide important insight into trends in the public’s knowledge, attitudes, and beliefs surrounding e-cigarettes, and subsequently guide public health interventions. Objective Our aim was to establish a supervised machine learning algorithm to build predictive classification models that assess Twitter data for a range of factors related to e-cigarettes. Methods Manual content analysis was conducted for 17,098 tweets. These tweets were coded for five categories: e-cigarette relevance, sentiment, user description, genre, and theme. Machine learning classification models were then built for each of these five categories, and word groupings (n-grams) were used to define the feature space for each classifier. Results Predictive performance scores for classification models indicated that the models correctly labeled the tweets with the appropriate variables between 68.40% and 99.34% of the time, and the percentage of maximum possible improvement over a random baseline that was achieved by the classification models ranged from 41.59% to 80.62%. Classifiers with the highest performance scores that also achieved the highest percentage of the maximum possible improvement over a random baseline were Policy/Government (performance: 0.94; % improvement: 80.62%), Relevance (performance: 0.94; % improvement: 75.26%), Ad or Promotion (performance: 0.89; % improvement: 72.69%), and Marketing (performance: 0.91; % improvement: 72.56%). The most appropriate word-grouping unit (n-gram) was 1 for the majority of classifiers. Performance continued to marginally increase with the size of the training dataset of manually annotated data, but eventually leveled off. Even at low dataset sizes of 4000 observations, performance characteristics were fairly sound. Conclusions Social media outlets

Brief History of Anti-Doping.

Science.gov (United States)

Ljungqvist, Arne

2017-01-01

The fight against doping in sport as we know it today commenced by the creation of the International Olympic Committee (IOC) Medical Commission in 1961 following the death of a Danish cyclist during the Rome Olympic Games the year before. After a slow start, the fight got under way as from the early 1970s under the leadership of the IOC and of the International Association of Athletics Federations. Despite a lack of understanding and weak support even from the sports community, a series of measures were taken during the 1970s and 1980s which still form cornerstones of today's anti-doping strategy. In addition to information and education campaigns, the most important examples are the introduction of procedural rules for doping controls, the establishment and follow-up of a list of prohibited substances and methods, the accreditation of doping control laboratories, the introduction of in- and out-of-competition testing, rules for therapeutic use exemption, and the introduction of blood sampling. During the 1990s, the anti-doping fight gained increasing support both inside and outside the sport community. In order to harmonize the wide variety of rules that had developed both in sport organizations and at the domestic level and to promote anti-doping activities, the World Anti-Doping Agency (WADA) was jointly created by the Olympic movement and the public authorities in 1999. WADA is today carrying on the fight supported by the universally accepted WADA Code and an International Anti-Doping Convention under UNESCO. © 2017 S. Karger AG, Basel.

Does Online Sentiment Predict Stock Market Indices? The ARDL Bounds Tests Based on Sina-Microblog Data%网络舆情是否影响股市行情?基于新浪微博大数据的ARDL模型边限分析

Institute of Scientific and Technical Information of China (English)

陈云松; 严飞

2017-01-01

本文基于新浪微博大数据,分析互联网上的股市舆情是否影响真实世界中的股市行情.在梳理网络舆情,特别是微博影响股市的机制的基础上,我们利用具有"利好"和"利空"含义的股市术语的微博出现词频("热词指数"),生成股市的"微博信心指数"."格兰杰因果检验"和"自回归分布滞后模型"(ARDL)边限检验表明:在股市震荡期,早前三天内的"微博信心指数"有助于预测上证指数;"微博信心指数"和"上证指数"存在正向相关的均衡关系;在股市行情平稳期,以上的统计关联并不存在;网络舆情通过影响入市资金流进一步影响股市行情.%This study focuses on the relationship between online sentiment and the stock market as both play a significant role in modern life.More specifically, based on a time series analysis of Sina-Microblog data and SSE composite index data, this paper explores whether and how Sina-Microblog feeds affect stock market trends in China.We extracted the frequency of occurrence of stock market-related terms on Sina-Microblog to construct an indicator of online market sentiment.Considering the complexity of the effects of online sentiment on the process of decision-making, we divided the stock market into low volatility and high volatility to analyze the effects.Granger tests using the T-Y process and co-integration analyses based on bound tests using the ARDL model show that: 1) the indicator of online market sentiment in previous 1-3 days is a statistically significant predictor of the daily SSE composite index;2) there is long-term relationship between online market sentiment and the SSE composite index;3) the relationship is insignificant when the market volatility is low, and 4) the relationship is mediated by the capital flow into the stock market.As an empirical study of the online sentiment influences real economic and social consequences, this paper contributes to our understanding of the vital role that

Field-dependent BRST–antiBRST transformations in Yang–Mills and Gribov–Zwanziger theories

Directory of Open Access Journals (Sweden)

Pavel Yu. Moshin

2014-11-01

Full Text Available We introduce the notion of finite BRST–antiBRST transformations, both global and field-dependent, with a doublet λa, a=1,2, of anticommuting Grassmann parameters and find explicit Jacobians corresponding to these changes of variables in Yang–Mills theories. It turns out that the finite transformations are quadratic in their parameters. At the same time, exactly as in the case of finite field-dependent BRST transformations for the Yang–Mills vacuum functional, special field-dependent BRST–antiBRST transformations, with sa-potential parameters λa=saΛ induced by a finite even-valued functional Λ and by the anticommuting generators sa of BRST–antiBRST transformations, amount to a precise change of the gauge-fixing functional. This proves the independence of the vacuum functional under such BRST–antiBRST transformations. We present the form of transformation parameters that generates a change of the gauge in the path integral and evaluate it explicitly for connecting two arbitrary Rξ-like gauges. For arbitrary differentiable gauges, the finite field-dependent BRST–antiBRST transformations are used to generalize the Gribov horizon functional h, given in the Landau gauge, and being an additive extension of the Yang–Mills action by the Gribov horizon functional in the Gribov–Zwanziger model. This generalization is achieved in a manner consistent with the study of gauge independence. We also discuss an extension of finite BRST–antiBRST transformations to the case of general gauge theories and present an ansatz for such transformations.

Structural Changes of International Trade Flows under the Impact of Globalization

Directory of Open Access Journals (Sweden)

Anca Dachin

2006-08-01

Full Text Available Structural changes of international trade flows indicate modifications in competitiveness of countries, in terms of production, technological upgrading and exports under the pressure of globalization. The paper aims to point out sources of competitive advantages especially in manufacturing exports of different groups of countries. The focus is on the shifts in the structure of manufacturing in the European Union and their effects on international rankings in export performances. An important issue refers to the opportunities given by the enlargement of the European Union and their impact on EU trade structures.

Global vegetation-fire pattern under different land use and climate conditions

Science.gov (United States)

Thonicke, K.; Poulter, B.; Heyder, U.; Gumpenberger, M.; Cramer, W.

2008-12-01

Fire is a process of global significance in the Earth System influencing vegetation dynamics, biogeochemical cycling and biophysical feedbacks. Naturally ignited wildfires have long history in the Earth System. Humans have been using fire to shape the landscape for their purposes for many millenia, sometimes influencing the status of the vegetation remarkably as for example in Mediterranean-type ecosystems. Processes and drivers describing fire danger, ignitions, fire spread and effects are relatively well-known for many fire-prone ecosystems. Modeling these has a long tradition in fire-affected regions to predict fire risk and behavior for fire-fighting purposes. On the other hand, the global vegetation community realized the importance of disturbances to be recognized in their global vegetation models with fire being globally most important and so-far best studied. First attempts to simulate fire globally considered a minimal set of drivers, whereas recent developments attempt to consider each fire process separately. The process-based fire model SPITFIRE (SPread and InTensity of FIRE) simulates these processes embedded in the LPJ DGVM. Uncertainties still arise from missing measurements for some parameters in less-studied fire regimes, or from broad PFT classifications which subsume different fire-ecological adaptations and tolerances. Some earth observation data sets as well as fire emission models help to evaluate seasonality and spatial distribution of simulated fire ignitions, area burnt and fire emissions within SPITFIRE. Deforestation fires are a major source of carbon released to the atmosphere in the tropics; in the Amazon basin it is the second-largest contributor to Brazils GHG emissions. How ongoing deforestation affects fire regimes, forest stability and biogeochemical cycling in the Amazon basin under present climate conditions will be presented. Relative importance of fire vs. climate and land use change is analyzed. Emissions resulting from

Investigation of China’s national public relations strategy under globalization : the hotspots around the national media

OpenAIRE

雷, 紫雯

2014-01-01

This study investigates on China’s national public relations strategy under the globalization by analyzing the national media. In recent years, in order to improve the global public opinion environment, and to improve its national public relations capabilities that match its economic power status, China has actively strengthened its national public relations strategies, including making the national “media go out”, and building world-class media. By researching on the localization of Chinese ...

Globally COnstrained Local Function Approximation via Hierarchical Modelling, a Framework for System Modelling under Partial Information

DEFF Research Database (Denmark)

Øjelund, Henrik; Sadegh, Payman

2000-01-01

be obtained. This paper presents a new approach for system modelling under partial (global) information (or the so called Gray-box modelling) that seeks to perserve the benefits of the global as well as local methodologies sithin a unified framework. While the proposed technique relies on local approximations......Local function approximations concern fitting low order models to weighted data in neighbourhoods of the points where the approximations are desired. Despite their generality and convenience of use, local models typically suffer, among others, from difficulties arising in physical interpretation...... simultaneously with the (local estimates of) function values. The approach is applied to modelling of a linear time variant dynamic system under prior linear time invariant structure where local regression fails as a result of high dimensionality....

The discourse of liberation: Frames used in characterising the gay ...

African Journals Online (AJOL)

Kate H

frames to express anti-gay sentiments, the Mail & Guardian primarily used these ... it is often silenced among traditional sources of knowledge such as friends, ... suggested by Van Dijk (1991) in considering issues of language and power, the ...

Offering sanctuary to failed refugee claimants in Canada

Directory of Open Access Journals (Sweden)

Kristin Marshall

2014-11-01

Full Text Available Despite the anti-refugee sentiment demonstrated by Canada’s recent legislative changes and the government’s hardening attitude towards those in sanctuary, the spirit of resistance and community engagement is alive and well in Canada.

The production and sales of anti-tuberculosis drugs in China.

Science.gov (United States)

Huang, Yang-Mu; Zhao, Qi-Peng; Ren, Qiao-Meng; Peng, Dan-Lu; Guo, Yan

2016-10-04

Tuberculosis (TB) is a major infectious disease globally. Adequate and proper use of anti-TB drugs is essential for TB control. This study aims to study China's production capacity and sales situation of anti-TB drugs, and to further discuss the potential for China to contribute to global TB control. The production data of anti-TB drugs in China from 2011 to 2013 and the sales data from 2010 to 2014 were extracted from Ministry of Industry and Information Technology database of China and IMS Health database, respectively. The number of drugs was standardized to the molecular level of the key components before calculating. All data were described and analyzed by Microsoft Excel. First-line drugs were the majority in both sales (89.5 %) and production (92.3 %) of anti-TB drugs in China. The production of rifampicin held the majority share in active pharmaceutical ingredients (APIs) and finished products, whilst ethambutol and pyrazinamide were the top two sales in finished products. Fixed-dose combinations only held small percentages in total production and sales weight, though a slight increase was observed. The production and sales of streptomycin showed a tendency of decrease after 2012. The trends and proportion of different anti-TB drugs were similar in production and sales, however, the production weight was much larger than that of sales, especially for rifampicin and isoniazid. First-line drugs were the predominant medicine produced and used in China. While the low production and sales of the second-line TB drugs and FDCs rose concerns for the treatment of multiple drug resistant TB. The redundant production amount, as well as the prompt influence of national policy on drug production and sales, indicated the potential for China to better contribute to global TB control.

Trump, Brexit, Right-wing Anti-globalisation, and An Uncertain Future for Public Health

Science.gov (United States)

Macgregor-Bowles, Isabelle; Bowles, Devin C.

2017-01-01

Global public health is intimately linked with political, economic and social determinants. The current global order has been built on the assumption that the globalisation agenda shared by political elites of the last several decades will continue. Individuals, businesses and countries have all made decisions, many of them linked to health, based on this assumption. The election of Donald Trump to the US presidency and the vote in Britain to exit the European Union exemplify a recent wave of right-wing anti-globalisation, which has risen in much of the West. The right-wing anti-globalisation movement will substantially affect global health through four pathways. Restrictions on trade will dampen economic growth and could diminish food security and the availability of medical supplies. Xenophobia will harm mental health through the lived experience of minorities, and will elevate the risk of economic and military conflict between countries. Increased defence expenditure in a time of limited government budgets will constrict funding available for healthcare and the social determinants of health. Mistrust of international treaties, including for climate change, will undermine the Paris Agreement and hasten greenhouse gas emissions. Without rapid mitigation, climate change could devastate population health globally through a range of mechanisms, including diminished food security and increased violent conflict. These would amplify many of the other health effects of right-wing anti-globalisation. By emphasising the shared humanity of all people, population health offers an antidote to the narrow focus of right-wing anti-globalisation. PMID:29546210

Trump, Brexit, Right-wing Anti-globalisation, and An Uncertain Future for Public Health.

Science.gov (United States)

Macgregor-Bowles, Isabelle; Bowles, Devin C

2017-01-01

Global public health is intimately linked with political, economic and social determinants. The current global order has been built on the assumption that the globalisation agenda shared by political elites of the last several decades will continue. Individuals, businesses and countries have all made decisions, many of them linked to health, based on this assumption. The election of Donald Trump to the US presidency and the vote in Britain to exit the European Union exemplify a recent wave of right-wing anti-globalisation, which has risen in much of the West. The right-wing anti-globalisation movement will substantially affect global health through four pathways. Restrictions on trade will dampen economic growth and could diminish food security and the availability of medical supplies. Xenophobia will harm mental health through the lived experience of minorities, and will elevate the risk of economic and military conflict between countries. Increased defence expenditure in a time of limited government budgets will constrict funding available for healthcare and the social determinants of health. Mistrust of international treaties, including for climate change, will undermine the Paris Agreement and hasten greenhouse gas emissions. Without rapid mitigation, climate change could devastate population health globally through a range of mechanisms, including diminished food security and increased violent conflict. These would amplify many of the other health effects of right-wing anti-globalisation. By emphasising the shared humanity of all people, population health offers an antidote to the narrow focus of right-wing anti-globalisation.

Designing Supervision under the Preventive Anti-Money Laundering Policy in the European Union

Directory of Open Access Journals (Sweden)

Melissa van den Broek

2014-12-01

Full Text Available Directive 2005/60/EC on the prevention of the use of the financial system for the purpose of money laundering and terrorist financing is currently one of the main instruments which regulates efforts to combat money laundering (and terrorist financing in the European Union. Respecting national procedural autonomy, this directive leaves a high degree of freedom for the Member States in designing their own supervisory architectures under the preventive anti-money laundering policy. This contribution adopts a systematic approach to the institutional differences between the EU Member States and presents four models of supervision that are currently present in the European Union. It explains the main characteristics of these models, categorises the EU Member States accordingly and analyses the potential strengths and weaknesses of each model, thereby providing a first indication of their effectiveness.

Facing aliens under globalization: changing meanings of home for Taiwanese employers of foreign domestics.

Science.gov (United States)

Cheng, Shu-Ju Ada

2005-01-01

This paper is concerned with changing meanings of home for Taiwanese employers of foreign domestics under globalization. Shifting sense of home occurs for Taiwanese employers as well as foreign domestics in the process of labor migration. The author argues that Taiwanese employers, facing aliens at home, have adopted various rhetorical strategies to redefine their relationships with foreign domestics and deployed diverse practices of management within their households. As foreign domestics do housework at home, Taiwanese employers also do their own "homework," struggling to understand and cope with the process of becoming and being household employers. Their "homework" is an integral part of the globalization of domestic service.

Islamophobia and Public Health in the United States.

Science.gov (United States)

Samari, Goleen

2016-11-01

Anti-Muslim sentiments are increasingly common globally and in the United States. The recent rise in Islamophobia calls for a public health perspective that considers the stigmatized identity of Muslim Americans and health implications of Islamophobic discrimination. Drawing on a stigma, discrimination, and health framework, I expand the dialogue on the rise of Islamophobia to a discussion of how Islamophobia affects the health of Muslim Americans. Islamophobia can negatively influence health by disrupting several systems-individual (stress reactivity and identity concealment), interpersonal (social relationships and socialization processes), and structural (institutional policies and media coverage). Islamophobia deserves attention as a source of negative health outcomes and health disparities. Future public health research should explore the multilevel and multidimensional pathways between Islamophobia and population health.

Corruption kills: estimating the global impact of corruption on children deaths.

Science.gov (United States)

Hanf, Matthieu; Van-Melle, Astrid; Fraisse, Florence; Roger, Amaury; Carme, Bernard; Nacher, Mathieu

2011-01-01

Information on the global risk factors of children mortality is crucial to guide global efforts to improve survival. Corruption has been previously shown to significantly impact on child mortality. However no recent quantification of its current impact is available. The impact of corruption was assessed through crude Pearson's correlation, univariate and multivariate linear models coupling national under-five mortality rates in 2008 to the national "perceived level of corruption" (CPI) and a large set of adjustment variables measured during the same period. The final multivariable model (adjusted R(2)= 0.89) included the following significant variables: percentage of people with improved sanitation (p.valueCorruption Perception Index (p.valuecorruption) was associated with an increase in the log of national under-five mortality rate of 0.0644. According to this result, it could be roughly hypothesized that more than 140000 annual children deaths could be indirectly attributed to corruption. Global response to children mortality must involve a necessary increase in funds available to develop water and sanitation access and purchase new methods for prevention, management, and treatment of major diseases drawing the global pattern of children deaths. However without paying regard to the anti-corruption mechanisms needed to ensure their proper use, it will also provide further opportunity for corruption. Policies and interventions supported by governments and donors must integrate initiatives that recognise how they are inter-related.

Role of innovative technologies under the global zero emissions scenarios

International Nuclear Information System (INIS)

Tokimatsu, Koji; Konishi, Satoshi; Ishihara, Keiichi; Tezuka, Tetsuo; Yasuoka, Rieko; Nishio, Masahiro

2016-01-01

Highlights: • We modeled a zero emissions scenario based on the A1T scenario of IPCC-SRES. • We conducted global modeling by minimizing costs of energy, biomass, and materials. • A variety of advanced technology innovations were considered and incorporated. • Results suggest that zero emissions scenario may be possible in this century. • We revealed energy supply structure under the zero emissions scenarios. - Abstract: This study investigated zero emissions scenarios with following two originalities compared to various existing studies. One is that we based on A1T society of SRES (Special Report on Emissions Scenario) of IPCC (Intergovernmental Panel on Climate Change) compared to existing studies on those of B1 or B2. The second one is that various innovative technologies were considered and incorporated, such as biomass energy with carbon capture and storage (BECCS), and advanced nuclear technologies including hydrogen or synfuel production. We conducted global modeling over the period 2010–2150 in which energy, materials, and biomass and foods supply costs were minimized by linear programming. We found following features of energy supply structure in A1T scenario. Since the electric demand in A1T scenario in 2100 is two times larger than the others, (1) renewable energy which solely produce electricity, nuclear, and fossil energy with CCS (FECCS) especially coal are main sources of electricity, (2) renewable which can supply heat, namely BECCS and geothermal, satisfies the sector, and (3) hydrogen from coal is introduced in transport sector. It can be concluded that the zero emission energy systems with global economic growth will be possible, by development and deployment of ambitious advanced energy technologies.

An anti-HBV anthraquinone from aciduric fungus Penicillium sp. OUCMDZ-4736 under low pH stress.

Science.gov (United States)

Jin, Yanzheng; Qin, Shidong; Gao, Hai; Zhu, Guoliang; Wang, Wei; Zhu, Weiming; Wang, Yi

2018-01-01

To obtain new bioactive natural products, the effect of acidic stress on the metabolites of an aciduric fungus was investigated. This fungus, Penicillium sp. OUCMDZ-4736, which was isolated from the sediment around roots of mangrove (Acanthus ilicifolius), produced different compounds and higher yields under pH 2.5 than under neutral conditions. Using spectroscopic analyses and calculations, three new anthraquinone derivatives (1-3) were isolated and identified from the acidic fermentation broth (pH 2.5) of OUCMDZ-4736. Compound 1 showed much stronger anti-hepatitis B virus activity than that of the positive control, lamivudine, strongly inhibiting HBsAg and HBeAg secretion from HepG2.2.15 cells. These results show that extremophiles are a valuable resource of bioactive compounds, and that pH regulation is an effective strategy to induce metabolite production in aciduric fungi.

Manager of financial globalization? The European Union in global anti-money laundering and international accounting standard setting

OpenAIRE

Hilgers, Sven

2014-01-01

How does the European Union (EU) perform in international financial regulation? According to various scholars the global financial architecture has been shaped by the USA and the EU. But whereas the USA is without doubt the dominant actor or even described as hegemon in writing the rules for the global political economy and global financial markets, the EU seems to be a special kind of actor. The European Union is not only one of the biggest single financial markets in the world but also has ...

Islamic Rulings on Warfare

National Research Council Canada - National Science Library

Aboul-Enein, Youssef

2004-01-01

The United States no doubt will be involved in the Middle East for many decades. To be sure, settling the Israeli-Palestinian dispute or alleviating poverty could help to stem the tides of Islamic radicalism and anti-American sentiment...

A global limit load solution for plates with surface cracks under combined end force and cross-thickness bending

International Nuclear Information System (INIS)

Lei Yuebao; Fox, Mike J.H.

2011-01-01

A global limit load solution for rectangular surface cracks in plates under combined end force and cross-thickness bending is derived, which allows any combination of positive/negative end force and positive/negative cross-thickness moment. The solution is based on the net-section plastic collapse concept and, therefore, gives limit load values based on the Tresca yielding criterion. Solutions for both cases with and without crack face contact are derived when whole or part of the crack is located in the compressive stress zone. From the solution, particular global limit load solutions for plates with extended surface cracks and through-thickness cracks under the same loading conditions are obtained. The solution is consistent with the limit load solution for surface cracks in plates under combined tension and positive bending due to Goodall and Webster and Lei when both the applied end force and bending moment are positive. The solution reduces to the limit load solution for plain plates under combined end force and cross-thickness bending when the crack vanishes. - Highlights: → A global limit load solution for plates with surface cracks in plates is derived. → Combined positive/negative end force and positive/negative cross-thickness moment are considered. → The solution is based on the net-section plastic collapse concept.

Religious ritual contested: anti-religious activities and women’s ritual practice in rural Soviet Karelia

Directory of Open Access Journals (Sweden)

Marja-Liisa Keinänen

2003-01-01

Full Text Available After the October Revolution, the Bolsheviks sought to establish a new atheistic order which would eradicate from the public consciousness all vestiges of "religious prejudices", which were regarded as a residue from the imperial era and an instrument used to exploit the masses. Even though it was generally held that religion would automatically disappear from socialist society when its material precondition, the class society, was abolished, the regime made concentrated efforts to speed up the process by means of virulent anti-religious propaganda. The ultimate goal was to wipe out the persistent remains of the bourgeois system of values. No force was to be used since it was feared this would merely offend the religious sentiments of the people and strengthen their adherence to religion. Theoretically, the ultimate goal was to be achieved through education and information, but in practice, anti-religious activities were at times quite brutal. These attacks were successful in curtailing the activities of religious institutions in Karelia, but did not bring to an end the religious practices of lay people, which were continued, in one form or another, throughout the entire Soviet period. One fundamental reason for the survival of religious rituals, both Christian and indigenous, was the fact that they were so deeply embedded in people's consciousness and intimately integrated with their everyday lives. Every important phase and turn in human life was sanctified by rituals. The goal of the present paper is to examine what forms anti-religious attacks took in Soviet Karelia and how people reacted to them. The focus is on the attacks against the very fundaments of the ritual complex of the church and, by extension, on the effects of these attacks on the indigenous ritual complex, which co-existed in parallel with that of the "official" religious institutions.

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

Science.gov (United States)

John B Kim; Erwan Monier; Brent Sohngen; G Stephen Pitts; Ray Drapek; James McFarland; Sara Ohrel; Jefferson Cole

2016-01-01

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a...

On Mathematical Anti-Evolutionism

Science.gov (United States)

Rosenhouse, Jason

2016-03-01

The teaching of evolution in American high schools has long been a source of controversy. The past decade has seen an important shift in the rhetoric of anti-evolutionists, toward arguments of a strongly mathematical character. These mathematical arguments, while different in their specifics, follow the same general program and rely on the same underlying model of evolution. We shall discuss the nature and history of this program and model and describe general reasons for skepticism with regard to any anti-evolutionary arguments based upon them. We shall then survey the major arguments used by anti-evolutionists, to show how our general considerations make it possible to quickly identify their weakest points.

Can risk communication provide assistance in nuclear energy disputes?

International Nuclear Information System (INIS)

Meadd, Ellen

2001-01-01

The continued use of nuclear technology in Canada appears to he limited by a lack of public acceptance of fuel waste disposal strategies. The outcome of the recent environmental assessment process conducted on the deep geological disposal concept bears-out this point. A brief review of transcripts from the he public hearing portion of this process indicates that public sentiment on the issue includes anti-nuclear attitudes and concern over equity, safety, and trust. This paper discusses Canadian sentiment on the issue and suggests that it is in line with public views on similar issues in other nations. The field of risk communication has played a significant role in understanding the root causes of public opposition. This paper suggests that the field is well-placed to play an expanded role in resolving the issues underlying public concerns, (e.g., lack of trust, public disenfranchisement with the decision making process); however, this is a supportive role. It is suggested that broad-based involvement, commitment, and collaboration among all stake holders in this dispute are necessary if improvement is to be achieved. (author)

Unpacking the Global Crisis

DEFF Research Database (Denmark)

Juego, Bonn; Schmidt, Johannes Dragsbæk

The paper hopes to contribute to a reading of the political economy of the current global crisis with a focus on four interrelated themes. First, we discuss the constitutive role and functional character of crises in the evolution of neo-liberalism in particular and in capitalist reproduction...... opposing crisis responses—from multilaterals to regional organisations to global civil society—and realise that responses from either pro-neoliberal or anti-neoliberal forces are fundamentally the same through the years, simply re-articulating analyses and programmes that they have respectively...... pursued and advocated long before the global crisis. And fourth, in the context of East and Southeast Asia, we examine the tendencies of the global crisis vis-à-vis the strengthening and even acceleration of emergent authoritarian liberalism in the region despite and because of the global crisis....

6 CFR 25.4 - Designation of qualified anti-terrorism technologies.

Science.gov (United States)

2010-01-01

... 6 Domestic Security 1 2010-01-01 2010-01-01 false Designation of qualified anti-terrorism... REGULATIONS TO SUPPORT ANTI-TERRORISM BY FOSTERING EFFECTIVE TECHNOLOGIES § 25.4 Designation of qualified anti-terrorism technologies. (a) General. The Under Secretary may Designate as a Qualified Anti-Terrorism...

Vittimizzazione e senso di insicurezza nei confronti del crimine: un'analisi empirica sul caso italiano / Criminal victimization and people's perception of safety: an Italian research / Victimisation criminelle et sentiment d'insécurité: une recherche empirique en Italie

Directory of Open Access Journals (Sweden)

Triventi Moris

2008-10-01

Full Text Available In this paper the relationship between criminal victimization and people’s perception of safety is explored. At first sight, the connection between these phenomena seems to be obvious: victims of a crime are probably more unsafe than non victimized people. However, many studies have found that the relationship between fear and crime is more complex than expected. In the first part of the paper the mixed research results are discussed and some reasons of this heterogeneity are identified. In the second part an analysis is conducted on data from the Italian Survey on Citizens’ Safety (Indagine sulla sicurezza dei cittadini. The main findings indicate that victimization affects both feelings of safety in the streets and in one’s own home, but with different intensity. Theft and snatch victimization is associated with safety in the streets, whereas burglary victimization with the perception of safety in one’s own home. Multivariate binomial regression models show that in Italy previous victimization contributes to increase the probability of feeling unsafe both in the streets and in one’s own home, all else being equal.Le but de cet article est d'analyser la relation entre l'expérience de victimisation et le sentiment d'insécurité collective. Au premier regard, la relation entre ces deux phénomènes peut sembler évidente: le sentiment d'insécurité est peut-être plus fort chez les victimes de crime que chez ceux qui n'ont jamais été frappés par le crime. Toutefois, beaucoup d'études ont montré que la relation entre l'insécurité et le crime est plus complexe qu'on ne l'avait prévu. Dans la première partie de cet article, nous discutons les résultats contradictoires des études mentionnées plus haut et identifions quelques-un des motifs de cette hétérogénéité. Dans la deuxième partie, nous effectuons une analyse sur les données de l'enquête italienne sur la sécurité des citoyens (Indagine sulla sicurezza dei

Permafrost degradation and associated ground settlement estimation under 2 °C global warming

Science.gov (United States)

Guo, Donglin; Wang, Huijun

2017-10-01

Global warming of 2 °C above preindustrial levels has been considered to be the threshold that should not be exceeded by the global mean temperature to avoid dangerous interference with the climate system. However, this global mean target has different implications for different regions owing to the globally nonuniform climate change characteristics. Permafrost is sensitive to climate change; moreover, it is widely distributed in high-latitude and high-altitude regions where the greatest warming is predicted. Permafrost is expected to be severely affected by even the 2 °C global warming, which, in turn, affects other systems such as water resources, ecosystems, and infrastructures. Using air and soil temperature data from ten coupled model intercomparison project phase five models combined with observations of frozen ground, we investigated the permafrost thaw and associated ground settlement under 2 °C global warming. Results show that the climate models produced an ensemble mean permafrost area of 14.01 × 106 km2, which compares reasonably with the area of 13.89 × 106 km2 (north of 45°N) in the observations. The models predict that the soil temperature at 6 m depth will increase by 2.34-2.67 °C on area average relative to 1990-2000, and the increase intensifies with increasing latitude. The active layer thickness will also increase by 0.42-0.45 m, but dissimilar to soil temperature, the increase weakens with increasing latitude due to the distinctly cooler permafrost at higher latitudes. The permafrost extent will obviously retreat north and decrease by 24-26% and the ground settlement owing to permafrost thaw is estimated at 3.8-15 cm on area average. Possible uncertainties in this study may be mostly attributed to the less accurate ground ice content data and coarse horizontal resolution of the models.

anti B{sup 0}, B{sup -} and anti B{sub s}{sup 0} decays into J/ψ and K anti K or πη

Energy Technology Data Exchange (ETDEWEB)

Liang, Wei-Hong [Guangxi Normal University, Department of Physics, Guilin (China); Xie, Ju-Jun [Chinese Academy of Sciences, Institute of Modern Physics, Lanzhou (China); Chinese Academy of Sciences, State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Beijing (China); Oset, E. [Chinese Academy of Sciences, Institute of Modern Physics, Lanzhou (China); Centro Mixto Universidad de Valencia-CSIC Institutos de Investigacion de Paterna, Departamento de Fisica Teorica y IFIC, Valencia (Spain)

2015-12-15

We study the anti B{sub s}{sup 0} → J/ψK{sup +}K{sup -}, anti B{sup 0} → J/ψK{sup +}K{sup -}, B{sup -} → J/ψK{sup 0}K{sup -}, anti B{sup 0} → J/ψπ{sup 0}η and B{sup -} → J/ψπ{sup -}η decays and compare their mass distributions with those obtained for the anti B{sub s}{sup 0} → J/ψπ{sup +}π{sup -} and anti B{sup 0} → J/ψπ{sup +}π{sup -}. The approach followed consist in a factorization of the weak part and the hadronization part into a factor which is common to all the processes. Then what makes the reactions different are some trivial Cabibbo-Kobayashi-Maskawa matrix elements and the weight by which the different pairs of mesons appear in a primary step plus their final state interaction. These elements are part of the theory and thus, up to a global normalization factor, all the invariant mass distributions are predicted with no free parameters. Comparison is made with the limited experimental information available. Further comparison of these results with coming LHCb measurements will be very valuable to make progress in our understanding of the meson.meson interaction and the nature of the low lying scalar meson resonances, f{sub 0}(500), f{sub 0}(980) and a{sub 0}(980). (orig.)

Germination Shifts of C3 and C4 Species under Simulated Global Warming Scenario

Science.gov (United States)

Zhang, Hongxiang; Yu, Qiang; Huang, Yingxin; Zheng, Wei; Tian, Yu; Song, Yantao; Li, Guangdi; Zhou, Daowei

2014-01-01

Research efforts around the world have been increasingly devoted to investigating changes in C3 and C4 species' abundance or distribution with global warming, as they provide important insight into carbon fluxes and linked biogeochemical cycles. However, changes in the early life stage (e.g. germination) of C3 and C4 species in response to global warming, particularly with respect to asymmetric warming, have received less attention. We investigated germination percentage and rate of C3 and C4 species under asymmetric (+3/+6°C at day/night) and symmetric warming (+5/+5°C at day/night), simulated by alternating temperatures. A thermal time model was used to calculate germination base temperature and thermal time constant. Two additional alternating temperature regimes were used to test temperature metrics effect. The germination percentage and rate increased continuously for C4 species, but increased and then decreased with temperature for C3 species under both symmetric and asymmetric warming. Compared to asymmetric warming, symmetric warming significantly overestimated the speed of germination percentage change with temperature for C4 species. Among the temperature metrics (minimum, maximum, diurnal temperature range and average temperature), maximum temperature was most correlated with germination of C4 species. Our results indicate that global warming may favour germination of C4 species, at least for the C4 species studied in this work. The divergent effects of asymmetric and symmetric warming on plant germination also deserve more attention in future studies. PMID:25137138

Germination shifts of C3 and C4 species under simulated global warming scenario.

Science.gov (United States)

Zhang, Hongxiang; Yu, Qiang; Huang, Yingxin; Zheng, Wei; Tian, Yu; Song, Yantao; Li, Guangdi; Zhou, Daowei

2014-01-01

Research efforts around the world have been increasingly devoted to investigating changes in C3 and C4 species' abundance or distribution with global warming, as they provide important insight into carbon fluxes and linked biogeochemical cycles. However, changes in the early life stage (e.g. germination) of C3 and C4 species in response to global warming, particularly with respect to asymmetric warming, have received less attention. We investigated germination percentage and rate of C3 and C4 species under asymmetric (+3/+6°C at day/night) and symmetric warming (+5/+5°C at day/night), simulated by alternating temperatures. A thermal time model was used to calculate germination base temperature and thermal time constant. Two additional alternating temperature regimes were used to test temperature metrics effect. The germination percentage and rate increased continuously for C4 species, but increased and then decreased with temperature for C3 species under both symmetric and asymmetric warming. Compared to asymmetric warming, symmetric warming significantly overestimated the speed of germination percentage change with temperature for C4 species. Among the temperature metrics (minimum, maximum, diurnal temperature range and average temperature), maximum temperature was most correlated with germination of C4 species. Our results indicate that global warming may favour germination of C4 species, at least for the C4 species studied in this work. The divergent effects of asymmetric and symmetric warming on plant germination also deserve more attention in future studies.

Discussion on anti-flood renovation of operational nuclear power plants

International Nuclear Information System (INIS)

Chen Jiangang; Chen Haiqiao; Zhang Lihan; Wang Sen; Liu Shifeng

2014-01-01

The design of nuclear power plants on anti-flood performance was only based on design basis condition in China. The Fukushima nuclear accident revealed the possibility of suffering flood under beyond design basis condition, which caused the continuously deterioration of Fukushima nuclear accident. After the accident, China national nuclear safety regulators proposed new requirements on performance of anti-flood of nuclear power plants. Then, Qinshan Phase II carried out research of anti-flood technology. This paper introduced the background, research and development of anti-flood renovation technology for important safety buildings of Qinshan Phase II, and discussed the necessary for improvement of anti-flood capacity of nuclear power plants and relative measures in China, which is helpful to improve anti-flood performance of operational nuclear power plants and nuclear power plants under construction. (authors)

Spring and Its Global Echo: Quantitative Analysis

Directory of Open Access Journals (Sweden)

A. V. Korotayev

2017-01-01

Full Text Available It is shown that the Arab Spring acted as a trigger for a global wave of socio-political destabilization, which signifi cantly exceeded the scale of the Arab Spring itself and affected absolutely all world-system zones. Only in 2011 the growth of the global number of largescale anti-government demonstrations, riots and political strikes was to a high degree (although not entirely due to their growth in the Arab world. In the ensuing years, the Arab countries rather made a negative contribution to a very noticeable further increase in the global number of large-scale anti-government demonstrations, riots and general strikes (the global intensity of all these three important types of socio-political destabilization continued to grow despite the decline in the Arab world. Thus, for all these three important indicators of sociopolitical destabilization, the scale of the global echo of the Arab Spring has overshadowed the scale of the Arab Spring itself. Only as regards the fourth considered indicator (major terrorist attacks / guerrilla warfare the scale of the global echo for the entire period considered did not overshadow the scale of the Arab Spring (and, incidentally, «Winter» - and in 2014-2015 Arab countries continued to make a disproportionate contribution to the historically record global values of this sad indicator – global number of major terrorist attacks/ guerilla warfare. To conclude, triggered by the Arab Spring, the global wave of socio-political destabilization led after 2010 to a very signifi cant growth of socio-political instability in absolutely all World System zones. However, this global destabilization wave manifested itself in different World System zones in different ways and not completely synchronously.

The Power of Performance Indices in the Global Politics of Anti-corruption

DEFF Research Database (Denmark)

Krause Hansen, Hans

2012-01-01

. Drawing on studies of organisation, surveillance and governmentality, this article examines the capacity of performance indices to construct comparable and governable subjects in international efforts to combat corruption. It conceptualises performance indices in terms of technologies of distance......While scholars have focused on the macro-structural, institutional and legal dimensions at work in international anti-corruption, they have paid little attention to role of the more specific technologies through which social forces become entangled in efforts at combating corruption internationally......, communication and surveillance and analyses a variety of corruption and anti-corruption indices, including corporate blacklisting as applied by the World Bank towards fraudulent corporations. It demonstrates how performance indices are implicated in the construction of standards and scripts for action against...

Trump, Brexit, Right-wing Anti-globalisation, and An Uncertain Future for Public Health

Directory of Open Access Journals (Sweden)

2017-04-01

Full Text Available Global public health is intimately linked with political, economic and social determinants. The current global order has been built on the assumption that the globalisation agenda shared by political elites of the last several decades will continue. Individuals, businesses and countries have all made decisions, many of them linked to health, based on this assumption. The election of Donald Trump to the US presidency and the vote in Britain to exit the European Union exemplify a recent wave of right-wing anti-globalisation, which has risen in much of the West. The right-wing anti-globalisation movement will substantially affect global health through four pathways. Restrictions on trade will dampen economic growth and could diminish food security and the availability of medical supplies. Xenophobia will harm mental health through the lived experience of minorities, and will elevate the risk of economic and military conflict between countries. Increased defence expenditure in a time of limited government budgets will constrict funding available for healthcare and the social determinants of health. Mistrust of international treaties, including for climate change, will undermine the Paris Agreement and hasten greenhouse gas emissions. Without rapid mitigation, climate change could devastate population health globally through a range of mechanisms, including diminished food security and increased violent conflict. These would amplify many of the other health effects of right-wing anti-globalisation. By emphasising the shared humanity of all people, population health offers an antidote to the narrow focus of right-wing anti-globalisation.

Globalization, Inequality, Say’s Law, and Fiscal Globalism

Directory of Open Access Journals (Sweden)

Gerasimos T. Soldatos

2017-07-01

Full Text Available This is a brief note maintaining that financial globalization has been faster than the integration of the remaining sectors of the world economy, thus encouraging wealth inequality, under-production, and under-consumption in line with Say’s Law. Financial investment has become more profitable than real investment, discouraging production ventures, and weakening labor’s relative income position and purchasing power. Moreover, this article works out a model of international government indirect tax competition as a policy means against increasing inequality. The mentality under which this tax policy paradigm is put forward is that the competition of nation states in a fiscal globalism fashion crystallizes the optimal level of centralization under globalism; optimal, that is, from the viewpoint of safeguarding against the manipulation of world markets by financiers.

Global assessment of river flood protection benefits and corresponding residual risks under climate change

Science.gov (United States)

Lim, Wee Ho; Yamazaki, Dai; Koirala, Sujan; Hirabayashi, Yukiko; Kanae, Shinjiro; Dadson, Simon J.; Hall, Jim W.

2016-04-01

substantially when flood protection level exceeds 20 years. These findings might be useful for decision-makers to weight the size of water infrastructure investment and emergency response capacity under climate change. References: Arnell, N.W, Gosling, S.N., 2014. The impact of climate change on river flood risk at the global scale. Climatic Change 122: 127-140, doi: 10.1007/s10584-014-1084-5. Hirabayashi et al., 2013. Global flood risk under climate change. Nature Climate Change 3: 816-821, doi: 10.1038/nclimate1911. Jongman et al., 2015. Declining vulnerability to river floods and the global benefits of adaptation. Proceedings of National Academy of the United States of America 112, E2271-E2280, doi: 10.1073/pnas.1414439112. Sadoff et al., 2015. Securing Water, Sustaining Growth: Report of the GWP/OECD Task Force on Water Security and Sustainable Growth, University of Oxford, UK, 180 pp. Yamazaki et al., 2011. A physically based description of floodplain inundation dynamics in a global river routing model. Water Resources Research 47, W04501, doi: 10.1029/2010wr009726. Yamazaki et al., 2014. Development of the Global Width Database for Large Rivers. Water Resources Research 50, 3467-3480, doi: 10.1002/2013WR014664.

Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

Science.gov (United States)

Varlamova, Eugenia V.; Solovyev, Vladimir S.

2017-11-01

Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

The OECD Anti-Bribery Convention: Changing the Currents of Trade

OpenAIRE

D'Souza, Anna

2009-01-01

This paper examines how criminalizing the act of bribing a foreign public official affects international trade flows using a watershed global anti-corruption initiative – the 1997 OECD Anti-Bribery Convention. This multilateral agreement criminalized foreign bribery (previously illegal only for U.S. firms) in countries that represent over 75% of world exports. I exploit temporal variation in the implementation of the Convention along with variation in the level of corruption of importing coun...

Generalization of a global model for reinforced concrete beams under combined axial force and bending moments

International Nuclear Information System (INIS)

Bairrao, R.; Millard, A.; Barbe, B.

1991-01-01

A large set of numerical data was obtained using a program recently developed. From the various results achieved, new analytical expressions for the definition of damage and plasticity criteria are being derived. The importance of taking into account the presence of general bending was highlighted. The extension to 3D bending, of the previous global models for reinforced concrete beams under combined axial force and bending, is under development. (author)

Who is Less Welcome?: The Impact of Individuating Cues on Attitudes towards Immigrants

NARCIS (Netherlands)

Turper, Sedef; Iyengar, Shanto; Aarts, Kees; van Gerven-Haanpää, Minna Marja-Leena

2014-01-01

Based on a novel experimental design, the current study examines the impact of economic and cultural characteristics of potential immigrants on anti-immigrant sentiments. We investigate the extent to which individuating cues affect public support for individual immigrants in the USA and the

Attitudes toward blacks in the Obama era changing distributions and impacts on job approval and electoral choice, 2008-2012

NARCIS (Netherlands)

Pasek, Josh; Stark, Tobias; Krosnick, Jon A.; Tompson, Trevor; Payne, B. Keith

2014-01-01

Much published research indicates that voting behavior in the 2008 presidential election and evaluations of Barack Obama were importantly influenced by anti-Black sentiment. Various psychological theories made opposing predictions as to whether exposure to the first Black president during his first

The stage performance of Peer Gynt in Mysore: is 'global Ibsen' against globalization?

Directory of Open Access Journals (Sweden)

Sabiha Huq

2015-02-01

Full Text Available This article discusses an adaptation of Peer Gynt in the Kannada language, which was staged in the state of Karnataka, India in 1995. The director of the play asserted his concern of Western notion of interculturalism that is inevitably affected by the process of economic globalization, and according to him India has a different situation as there is ‘tremendous resistance’ to the homogenizing, commoditizing, and anti-democratic tendencies of globalization. Popular terms like ‘technology transfers’, ‘free trade’, ‘democracy’ etc., that are connected with globalization are criticized in the production and it is strongly rooted in serious issues like communal conflict and economic exploitation in contemporary India, providing a notion that globalization is a red herring to divert people from local realities. The analysis of the performance text and the images from the stage performance show how the creative forces behind this production were deeply preoccupied with the notion of the global vs. the national.

Integrated assessment of global water scarcity over the 21st century under multiple climate change mitigation policies

Energy Technology Data Exchange (ETDEWEB)

Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.; Kyle, G. Page; Davies, Evan; Chaturvedi, Vaibhav; Wise, Marshall A.; Patel, Pralit L.; Eom, Jiyong; Calvin, Katherine V.

2014-08-01

Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change and climate mitigation policies, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5 o x 0.5o resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W/m2 (equivalent to the SRES A1Fi emission scenario) and three climate policy scenarios with increasing mitigation stringency of 7.7, 5.5, and 4.2 W/m2 (equivalent to the SRES A2, B2, and B1 emission scenarios, respectively), we investigate the effects of emission mitigation policies on water scarcity. Two carbon tax regimes (a universal carbon tax (UCT) which includes land use change emissions, and a fossil fuel and industrial emissions carbon tax (FFICT) which excludes land use change emissions) are analyzed. The baseline scenario results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Additionally, in years 2050 and 2095, 36% (28%) and 44% (39%) of the global population, respectively, is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). When comparing the climate policy scenarios to the baseline scenario while maintaining

Dual anti-inflammatory and anti-parasitic action of topical ivermectin 1% in papulopustular rosacea.

Science.gov (United States)

Schaller, M; Gonser, L; Belge, K; Braunsdorf, C; Nordin, R; Scheu, A; Borelli, C

2017-11-01

Recently, therapy of rosacea with inflammatory lesions (papulopustular) has improved substantially with the approval of topical ivermectin 1% cream. It is assumed to have a dual mode of action with anti-inflammatory capacities and anti-parasitic effects against Demodex, which however has not yet been demonstrated in vivo. To find scientific rationale for the dual anti-inflammatory and anti-parasitic mode of action of topical ivermectin 1% cream in patients with rosacea. A monocentric pilot study was performed including 20 caucasion patients with moderate to severe rosacea, as assessed by investigator global assessment (IGA score ≥3) and a Demodex density ≥15/cm 2 . Patients were treated with topical ivermectin 1% cream once daily (Soolantra ® ) for ≥12 weeks. The density of Demodex mites was assessed with skin surface biopsies. Expression of inflammatory and immune markers was evaluated with RT-PCR and by immunofluorescence staining. The mean density of mites was significantly decreased at week 6 and week 12 (P < 0.001). The gene expression levels of IL-8, LL-37, HBD3, TLR4 and TNF-α were downregulated at both time points. Reductions in gene expression were significant for LL-37, HBD3 and TNF-α at both follow-up time points and at week 12 for TLR4 (all P < 0.05). Reduced LL-37 expression (P < 0.05) and IL-8 expression were confirmed on the protein level by immunofluorescence staining. All patients improved clinically, and 16 of 20 patients reached therapeutic success defined as IGA score ≤1. Topical ivermectin 1% cream acts by a dual, anti-inflammatory and anti-parasitic mode of action against rosacea by killing Demodex spp. in vivo, in addition to significantly improving clinical signs and symptoms in the skin. © 2017 European Academy of Dermatology and Venereology.

Receptindløst anti-osteoporotisk behandling i Danmark

DEFF Research Database (Denmark)