WorldWideScience

Sample records for underlying anti-globalization sentiments

  1. Nuclear position in power generation sector - under the pressure of anti-global warming and power market reform

    International Nuclear Information System (INIS)

    Hayashi, Taizo

    2005-01-01

    The future structure surrounding fuel choice in power generation sector should be understood how to evaluate actual and potential merit and demerit both in economic and environmental aspects on nuclear power generation. That is i.e. nuclear can be understood as superior power source without GHGs and on the other hand, as unfavorable power source which might cause some critical dangers due to its hazardous radioactive nuclear waste. On this specific characteristic, this theme on fuel choice surrounding nuclear in power generation sector could be understood as a highly cultural problem as much as economic and political one. For instance, we can observe quite opposite direction with each other on nuclear power development in European countries like France and Finland on one hand and Germany and Sweden on the other hand. Looking at Asian countries, we also observe the very reality of high economic growth with rapid growth of electricity demand like China. What on earth, is it really possible without nuclear power source for such gigantic countries. I will develop my personal idea on nuclear power source based on Japanese experience towards successfully managing nuclear power technologies in the world, consisting of developing countries with growing economies and of advanced ones with rather matured nuclear technology under the pressure of environmentally restricted world order. My basic view point to discuss nuclear power problem has, conclusionally speaking, several aspects; The first one is in the relation with deregulation or liberalization of electricity market, which has been undergoing among such developed countries as OECD member countries i.e. USA, EU, Japan and other countries. Deregulation or liberalization of electricity market seems to be the inevitable process towards more matured market economy among developed countries group, and that process inevitably forces management of power companies towards more near sighted attitude if those companies are

  2. 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......, Davis discusses the meanings of age and ageing, intergenerational conflicts, gender, and the impact of the body and social context on the experience of ageing. In drawing on both sentimental and naturalist themes and combining them, Davis’s stories reflect conflicting notions about ageing and old age...

  3. 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...

  4. Naturalizing sentimentalism for environmental ethics

    DEFF Research Database (Denmark)

    Kasperbauer, Tyler Joshua

    2015-01-01

    Jesse Prinz and Shaun Nichols have argued that within metaethics, sentimentalism is the theory that best accords with empirical facts about human moral psychology. Recent findings in experimental moral psychology, they argue, indicate that emotions are psychologically central to our moral concepts....... 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......, no supporters of sentimentalist accounts of environmental values have evaluated the empirical adequacy of their claims. The relevant evidence falls under two broad categories: (1) responses to nature itself and (2) moral evaluations of environmental behaviors. The evidence indicates that both valuing...

  5. Sentiment of Emojis.

    Directory of Open Access Journals (Sweden)

    Petra Kralj Novak

    Full Text Available There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. But what are their emotional contents? We provide the first emoji sentiment lexicon, called the Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of the emojis is computed from the sentiment of the tweets in which they occur. We engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive. About 4% of the annotated tweets contain emojis. The sentiment analysis of the emojis allows us to draw several interesting conclusions. It turns out that most of the emojis are positive, especially the most popular ones. The sentiment distribution of the tweets with and without emojis is significantly different. The inter-annotator agreement on the tweets with emojis is higher. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. We observe no significant differences in the emoji rankings between the 13 languages and the Emoji Sentiment Ranking. Consequently, we propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and a novel visualization in the form of a sentiment bar.

  6. Sentiment of Emojis.

    Science.gov (United States)

    Kralj Novak, Petra; Smailović, Jasmina; Sluban, Borut; Mozetič, Igor

    2015-01-01

    There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. But what are their emotional contents? We provide the first emoji sentiment lexicon, called the Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of the emojis is computed from the sentiment of the tweets in which they occur. We engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive). About 4% of the annotated tweets contain emojis. The sentiment analysis of the emojis allows us to draw several interesting conclusions. It turns out that most of the emojis are positive, especially the most popular ones. The sentiment distribution of the tweets with and without emojis is significantly different. The inter-annotator agreement on the tweets with emojis is higher. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. We observe no significant differences in the emoji rankings between the 13 languages and the Emoji Sentiment Ranking. Consequently, we propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and a novel visualization in the form of a sentiment bar.

  7. 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.

  8. Sapiness–sentiment analyser

    Directory of Open Access Journals (Sweden)

    Jánosi-Rancz Katalin Tünde

    2015-12-01

    Full Text Available In our ever-evolving world, the importance of social networks is bigger now than ever. The purpose of this paper is to develop a sentiment analyzer for the Hungarian language, which we can then use to analyze any text and conduct further experiments. One such experiment is an application which can interface with social networks, and run sentiment analysis on the logged-in users friends’ posts and comments, while the other experiment is the use of sentiment analysis in order to visualize the evolution of relationships between characters in a text.

  9. Machine learning in sentiment reconstruction of the simulated stock market

    Science.gov (United States)

    Goykhman, Mikhail; Teimouri, Ali

    2018-02-01

    In this paper we continue the study of the simulated stock market framework defined by the driving sentiment processes. We focus on the market environment driven by the buy/sell trading sentiment process of the Markov chain type. We apply the methodology of the Hidden Markov Models and the Recurrent Neural Networks to reconstruct the transition probabilities matrix of the Markov sentiment process and recover the underlying sentiment states from the observed stock price behavior. We demonstrate that the Hidden Markov Model can successfully recover the transition probabilities matrix for the hidden sentiment process of the Markov Chain type. We also demonstrate that the Recurrent Neural Network can successfully recover the hidden sentiment states from the observed simulated stock price time series.

  10. Sentiment, Care, and Respect

    Science.gov (United States)

    Darwall, Stephen

    2010-01-01

    Michael Slote proposes a rethinking of moral education from the perspective of a normative ethics of care combined with his distinctive sentimentalist metaethics. I raise questions concerning the role of empathy in Slote's picture and argue that empathy is related to respect and sentiments through which we hold ourselves and one another…

  11. What is Sentiment Analysis?

    Indian Academy of Sciences (India)

    Projecting as a computational problem, given a set of documents, sentences or phrases T by single or multiple authors that contain information regarding an Entity E, find the sentiment about E in each t \\in T. This can be solved by combined approach using Natural Language processing, Machine Learning, data mining and ...

  12. The Royal Birth of 2013: Analysing and Visualising Public Sentiment in the UK Using Twitter

    OpenAIRE

    Nguyen, Vu Dung; Varghese, Blesson; Barker, Adam

    2013-01-01

    Analysis of information retrieved from microblogging services such as Twitter can provide valuable insight into public sentiment in a geographic region. This insight can be enriched by visualising information in its geographic context. Two underlying approaches for sentiment analysis are dictionary-based and machine learning. The former is popular for public sentiment analysis, and the latter has found limited use for aggregating public sentiment from Twitter data. The research presented in t...

  13. Sentiment topic mining based on comment tags

    Science.gov (United States)

    Zhang, Daohai; Liu, Xue; Li, Juan; Fan, Mingyue

    2018-03-01

    With the development of e-commerce, various comments based on tags are generated, how to extract valuable information from these comment tags has become an important content of business management decisions. This study takes HUAWEI mobile phone tags as an example using the sentiment analysis and topic LDA mining method. The first step is data preprocessing and classification of comment tag topic mining. And then make the sentiment classification for comment tags. Finally, mine the comments again and analyze the emotional theme distribution under different sentiment classification. The results show that HUAWEI mobile phone has a good user experience in terms of fluency, cost performance, appearance, etc. Meanwhile, it should pay more attention to independent research and development, product design and development. In addition, battery and speed performance should be enhanced.

  14. Sentiment of Emojis

    OpenAIRE

    Kralj Novak, Petra; Smailovi?, Jasmina; Sluban, Borut; Mozeti?, Igor

    2015-01-01

    There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. But what are their emotional contents? We provide the first emoji sentiment lexicon, cal...

  15. 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 i...

  16. 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...

  17. The Asymmetric Effects of Investor Sentiment

    DEFF Research Database (Denmark)

    Lutz, Chandler

    2016-01-01

    are asymmetric: During peak-to-trough periods of investor sentiment (sentiment contractions), high sentiment predicts low future returns for the cross section of speculative stocks and for the market overall, whereas the relationship between sentiment and future returns is positive but relatively weak during...

  18. Affective Computing and Sentiment Analysis

    CERN Document Server

    Ahmad, Khurshid

    2011-01-01

    This volume maps the watershed areas between two 'holy grails' of computer science: the identification and interpretation of affect -- including sentiment and mood. The expression of sentiment and mood involves the use of metaphors, especially in emotive situations. Affect computing is rooted in hermeneutics, philosophy, political science and sociology, and is now a key area of research in computer science. The 24/7 news sites and blogs facilitate the expression and shaping of opinion locally and globally. Sentiment analysis, based on text and data mining, is being used in the looking at news

  19. 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

  20. From Sentiment to Sentimentality: A Nineteenth-Century Lexicographical Search

    Directory of Open Access Journals (Sweden)

    Marie Banfield

    2007-04-01

    Full Text Available The brief account of the lexicographical history of the word ‘sentiment' in the nineteenth century, and the table of definitions which follows it, grew from my increasing sense of the shifting and ambivalent nature of the term in the literature of the period, despite the resonance and the proverbial solidity of phrases such as ‘Victorian sentiment' and ‘Victorian sentimentality'. The table is self explanatory, representing the findings of a search, among a wide range of nineteenth-century dictionaries over the period, for the changing meanings accrued by the word ‘sentiment' over time, its extensions and its modifications. The nineteenth-century lexicographical history of the word ‘sentiment' has its chief roots in the Eighteenth-century enlightenment, with definitions from Samuel Johnson and quotations from John Locke, chiefly based on intellect and reason. The nineteenth century generated a number of derivatives of the word over a period of time to express altered modes of feeling, thought and moral concern. The history of the word ‘sentiment' offers a psychological as well as a linguistic narrative.

  1. 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

  2. From Emojis to Sentiment Analysis

    OpenAIRE

    Guibon , Gaël; Ochs , Magalie; Bellot , Patrice

    2016-01-01

    International audience; Studies on Twitter are becoming quite common these years. Even so, the majority of them did not focused on emoticons, even less on emojis. An overview of emoticons related work has been made recently [11]. However there is still too little research work related to emojis. In this paper we draw up the work and future approaches worth considering for emoji usage in Sentiment Analysis. We aim to put necessary theoretical background before using emojis for sentiment analys...

  3. SURVEY ON SENTIMENT ANALYSIS OF STOCK MARKET

    OpenAIRE

    Nausheen S; Anil Kumar M; Amrutha K K

    2017-01-01

    Sentiment analysis has seen a tremendous growth in the past few years. Sentiment analysis or opinion mining is a process of collecting users’ opinion from user generated content. It has various applications, such as stock market prediction, products’ review collection, etc. a large amount of work has been done in this field by applying sentiment analysis to various applications. The main goal of this paper is to study the various methods used for sentiment analysis. Further we explain the ove...

  4. 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...... results. The method should be seen as an alternative to pure machine learning methods for sentiment analysis, which are argued to have high difficulties in capturing long distance dependencies, and can be dependent on significant amount of domain specific training data. The results show that the method...

  5. Building domain specific sentiment lexicons combining information from many sentiment lexicons and a domain specific corpus

    OpenAIRE

    Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander; Engelstad, Paal E.

    2015-01-01

    Most approaches to sentiment analysis requires a sentiment lexicon in order to automatically predict sentiment or opinion in a text. The lexicon is generated by selecting words and assigning scores to the words, and the performance the sentiment analysis depends on the quality of the assigned scores. This paper addresses an aspect of sentiment lexicon generation that has been overlooked so far; namely that the most appropriate score assigned to a word in the lexicon is depen...

  6. Social Robots, fiction, and sentimentality

    DEFF Research Database (Denmark)

    Rodogno, Raffaele

    2016-01-01

    I examine the nature of human-robot pet relations that appear to involve genuine affective responses on behalf of humans towards entities, such as robot pets, that, on the face of it, do not seem to be deserving of these responses. Such relations have often been thought to involve a certain degree...... of sentimentality, the morality of which has in turn been the object of critical attention (Sparrow in Ethics Inf Technol 78:346–359, 2002; Blackford in Ethics Inf Technol 14:41–51, 2012). In this paper, I dispel the claim that sentimentality is involved in this type of relations. My challenge draws on literature...... of argument, however, I assume in the remaining part of the paper that sentimentality is indeed at play and bring to the fore aspects of its badness or viciousness that have not yet been discussed in connection with robot pets. I conclude that not even these aspects of sentimentality are at issue here. Yet, I...

  7. The Relationship between Sentiment and Risk in Financial Markets

    Directory of Open Access Journals (Sweden)

    Ana Luiza Paraboni

    2018-03-01

    Full Text Available This article estimates association coefficients between measures of market sentiment and risk in the U.S., German and Chinese markets. In terms of risk, four measures were considered: standard deviation, value at risk, expected shortfall and shortfall deviation risk. For market sentiment, data was collected using the Psych Signal technology, which is based on the behavior of investors on social networks. The results indicate significant statistical associations, with the direction of association having financial meaning. Moreover, the empirical findings are valid for all risk measurements. The results are in keeping with the Prospect Theory, since in moments when the sentiment indicates low liquidity (a negative value for the difference between Bullish and Bearish Intensities investors try to reduce the negotiation volume, which has a positive impact on risk. On the other hand, under the inverted scenario, when sentiment indicates high liquidity, there is an increase in the negotiation volume and a consequent decrease in risk. This article is important because its observations of market sentiment as measured by social media data show a consistent relationship with measures of financial risk.

  8. PARAMETRICAL WORDS IN THE SENTIMENT LEXICON

    Directory of Open Access Journals (Sweden)

    Elena Brunova

    2013-12-01

    Full Text Available In this paper, the main features of parametrical words within a sentiment lexicon are determined. The data for the research are client reviews in the Russian language taken from the bank client rating; the domain under study is bank service quality. The lexicon structure and the fragments from the lexicon database are presented. The sentiment lexicon includes two major classes (positive and negative words and three minor classes (increments, polarity modifiers, and polarity anti-modifiers. This lexicon is used as the main tool for the sentiment analysis carried out by two methods: the Naïve Bayes and the REGEX algorithms.Parametrical words are referred to as the words denoting the value of some domain-specific parameter, e.g. a battery life, or time of waiting. To distinguish the main features of parametrical words, the parameters relevant for the bank service quality domain are determined. The results of the research demonstrate that parametrical words can be ranged neither in the positive class, nor in the negative one. The words denoting the increase of a parameter should be ranged in the increment class, as they intensify positive or negative emotions. The words denoting the decrease of a parameter should be ranged in a new class which may be called the decrement class, as they reduce positive or negative emotions. The revised lexicon structure including the decrement class is proposed. The evident progress on the way to the lexicon universalization can be achieved by distinguishing two special classes for lexical increments and decrements. Another helpful idea is to extract bigrams or trigrams which could include parametrical words and the domain attributes they refer to.

  9. Twitter Sentiment Analysis of Movie Reviews using Machine Learning Techniques.

    OpenAIRE

    Akshay Amolik; Niketan Jivane; Mahavir Bhandari; Dr.M.Venkatesan

    2015-01-01

    Sentiment analysis is basically concerned with analysis of emotions and opinions from text. We can refer sentiment analysis as opinion mining. Sentiment analysis finds and justifies the sentiment of the person with respect to a given source of content. Social media contain huge amount of the sentiment data in the form of tweets, blogs, and updates on the status, posts, etc. Sentiment analysis of this largely generated data is very useful to express the opinion of the mass. Twitter sentiment a...

  10. 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.

  11. 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...... that housing sentiment explains a large share of the time-variation in house prices during both boom and bust cycles and it strongly outperforms several macroeconomic variables typically used to forecast house prices....

  12. MARKETING RESEARCH: THE ROLE OF SENTIMENT ANALYSIS

    OpenAIRE

    Meena Rambocas; João Gama

    2013-01-01

    This article promotes sentiment analysis as an alternative research technique for collecting and analyzing textual data on the internet. Sentiment analysis is a data mining technique that systematically evaluates textual content using machine learning techniques. As a research method in marketing, sentiment analysis presents an efficient and effective evaluation of consumer opinions in real time. It allows data collection and analysis from a very large sample without hindrances, obstructions ...

  13. Sentiment Analysis Challenges of Informal Arabic Language

    OpenAIRE

    Salihah AlOtaibi; Muhammad Badruddin Khan

    2017-01-01

    Recently, there are wide numbers of users that use the social network like Twitter, Facebook, MySpace to share various kinds of resources, express their opinions, thoughts, messages in real time. Thus, increase the amount of electronic content that generated by users. Sentiment analysis becomes a very interesting topic in research community. Thereby, we need to give more attention to Arabic sentiment analysis. This paper discusses the challenges and obstacles when analyze the sentiment analys...

  14. Tensor Fusion Network for Multimodal Sentiment Analysis

    OpenAIRE

    Zadeh, Amir; Chen, Minghai; Poria, Soujanya; Cambria, Erik; Morency, Louis-Philippe

    2017-01-01

    Multimodal sentiment analysis is an increasingly popular research area, which extends the conventional language-based definition of sentiment analysis to a multimodal setup where other relevant modalities accompany language. In this paper, we pose the problem of multimodal sentiment analysis as modeling intra-modality and inter-modality dynamics. We introduce a novel model, termed Tensor Fusion Network, which learns both such dynamics end-to-end. The proposed approach is tailored for the vola...

  15. Enhanced Twitter Sentiment Classification Using Contextual Information

    OpenAIRE

    Vosoughi, Soroush; Zhou, Helen L.; Roy, Deb K.

    2015-01-01

    The rise in popularity and ubiquity of Twitter has made sentiment analysis of tweets an important and well-covered area of research. However, the 140 character limit imposed on tweets makes it hard to use standard linguistic methods for sentiment classification. On the other hand, what tweets lack in structure they make up with sheer volume and rich metadata. This metadata includes geolocation, temporal and author information. We hypothesize that sentiment is d...

  16. The impact of investor sentiment on the German stock market

    OpenAIRE

    Finter, Philipp; Niessen-Ruenzi, Alexandra; Ruenzi, Stefan

    2011-01-01

    This paper develops a broad-based sentiment indicator for Germany and investigates whether investor sentiment can explain stock returns on the German stock market. Based on a principal component analysis, we construct a sentiment indicator that condenses information of several well-known sentiment proxies. We show that this indicator explains the return spread between sentiment sensitive stocks and stocks that are not sensitive to sentiment fluctuations. Specifically, stocks that are difficul...

  17. Temporal Causality Analysis of Sentiment Change in a Cancer Survivor Network.

    Science.gov (United States)

    Bui, Ngot; Yen, John; Honavar, Vasant

    2016-06-01

    use of an imperfect state transducer (in our case, the sentiment classifier). Our analysis of temporal causality of CSN sentiment dynamics offers new insights that the designers, managers and moderators of an online community such as CSN can utilize to facilitate and enhance the interactions so as to better meet the social support needs of the CSN participants. The proposed methodology for analysis of temporal causality has broad applicability in a variety of settings where the dynamics of the underlying system can be modeled in terms of state variables that change in response to internal or external inputs.

  18. 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.

  19. Using rhetorical structure in sentiment analysis

    NARCIS (Netherlands)

    Hogenboom, Alexander; Frasincar, Flavius; de Jong, Franciska M.G.; Kaymak, Uzay

    Automated sentiment analysis has become an active field of study with a broad applicability. One of the key open research issues lies in dealing with structural aspects of text when analyzing its conveyed sentiment. Recent work uses structural aspects of text in order to distinguish important text

  20. ARCHITECTURE OF A SENTIMENT ANALYSIS PLATFORM

    Directory of Open Access Journals (Sweden)

    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.

  1. Sentiments identitaires : le coeur des Wallons balance

    OpenAIRE

    Deflandre, Dimitri; Heselmans, Frédéric; Italiano, Patrick; Jacquemain, Marc

    2005-01-01

    L'article fait la synthèse d'une série d'enquêtes menées sur les sentiments d'appartenance des Wallons. Toutes les enquêtes pointent dans la même direction : ces sentiments d'appartenance sont complémentaires et non exclusifs.

  2. Sentimental Analysis for Airline Twitter data

    Science.gov (United States)

    Dutta Das, Deb; Sharma, Sharan; Natani, Shubham; Khare, Neelu; Singh, Brijendra

    2017-11-01

    Social Media has taken the world by surprise at a swift and commendable pace. With the advent of any kind of circumstances may it be related to social, political or current affairs the sentiments of people throughout the world are expressed through their help, making them suitable candidates for sentiment mining. Sentimental analysis becomes highly resourceful for any organization who wants to analyse and enhance their products and services. In the airline industries it is much easier to get feedback from astute data source such as Twitter, for conducting a sentiment analysis on their respective customers. The beneficial factors relating to twitter sentiment analysis cannot be impeded by the consumers who want to know the who’s who and what’s what in everyday life. In this paper we are classifying sentiment of Twitter messages by exhibiting results of a machine learning algorithm using R and Rapid Miner. The tweets are extracted and pre-processed and then categorizing them in neutral, negative and positive sentiments finally summarising the results as a whole. The Naive Bayes algorithm has been used for classifying the sentiments of recent tweets done on the different airlines.

  3. The Asymmetric Predictive Effects of Investor Sentiment

    DEFF Research Database (Denmark)

    Lutz, Chandler

    that the relationship between sentiment and returns is asymmetric: during bear markets, high sentiment predicts low future returns for the cross-section of speculative stocks and the market overall while the relationship during bull markets is weak and often insignicant. Thus, the results suggest that sophisticated...

  4. Citation Sentiment Analysis in Clinical Trial Papers.

    Science.gov (United States)

    Xu, Jun; Zhang, Yaoyun; Wu, Yonghui; Wang, Jingqi; Dong, Xiao; Xu, Hua

    2015-01-01

    In scientific writing, positive credits and negative criticisms can often be seen in the text mentioning the cited papers, providing useful information about whether a study can be reproduced or not. In this study, we focus on citation sentiment analysis, which aims to determine the sentiment polarity that the citation context carries towards the cited paper. A citation sentiment corpus was annotated first on clinical trial papers. The effectiveness of n-gram and sentiment lexicon features, and problem-specified structure features for citation sentiment analysis were then examined using the annotated corpus. The combined features from the word n-grams, the sentiment lexicons and the structure information achieved the highest Micro F-score of 0.860 and Macro-F score of 0.719, indicating that it is feasible to use machine learning methods for citation sentiment analysis in biomedical publications. A comprehensive comparison between citation sentiment analysis of clinical trial papers and other general domains were conducted, which additionally highlights the unique challenges within this domain.

  5. 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...... of Michigan's consumer survey. We find that housing sentiment strongly outperforms several macroeconomic variables typically used to forecast house prices. An in-sample forecast regression using quarterly data over the period 1975-2014 shows that housing sentiment is able to explain 48 percent of next quarter......'s national house price growth. Out-of-sample forecast regressions yield similar results. The strong predictive power of the sentiment index is robust across forecast horizons and holds at the state-level....

  6. 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.......We use the returns on lottery-like stocks to construct a novel index for investor sentiment in the stock market. This new measure is closely related to previously developed sentiment indicators, but more accurately tracks speculative episodes over the sample period. Using our index, we find...... that the relationship between sentiment and returns is asymmetric: during bear markets, high sentiment predicts low future returns for the cross-section of speculative stocks and the market overall while the relationship during bull markets is weak and often insignificant. Thus, the results suggest that sophisticated...

  7. Assessing anti-American sentiment through social media analysis

    OpenAIRE

    Morales, David J.

    2016-01-01

    Approved for public release; distribution is unlimited This thesis examines the history of anti-Americanism as both a passing sentiment and an enduring ideology and how both can be detrimental to American security and future prosperity. It further explores the analytical methods for studying anti-Americanism, to include classic polling and social media analysis in an attempt to determine the reliability of each. This work attempts to bring to light the underlying motives for anti-American ...

  8. 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.......We use the returns on lottery-like stocks to construct a novel index for investor sentiment in the stock market. This new measure is closely related to previously developed sentiment indicators, but more accurately tracks speculative episodes over the sample period. Using our index, we find...

  9. 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.......We use the returns on lottery-like stocks to construct a novel index for investor sentiment in the stock market. This new measure is closely related to previously developed sentiment indicators, but more accurately tracks speculative episodes over the sample period. Using our index, we find...

  10. Large Scale Implementations for Twitter Sentiment Classification

    Directory of Open Access Journals (Sweden)

    Andreas Kanavos

    2017-03-01

    Full Text Available Sentiment Analysis on Twitter Data is indeed a challenging problem due to the nature, diversity and volume of the data. People tend to express their feelings freely, which makes Twitter an ideal source for accumulating a vast amount of opinions towards a wide spectrum of topics. This amount of information offers huge potential and can be harnessed to receive the sentiment tendency towards these topics. However, since no one can invest an infinite amount of time to read through these tweets, an automated decision making approach is necessary. Nevertheless, most existing solutions are limited in centralized environments only. Thus, they can only process at most a few thousand tweets. Such a sample is not representative in order to define the sentiment polarity towards a topic due to the massive number of tweets published daily. In this work, we develop two systems: the first in the MapReduce and the second in the Apache Spark framework for programming with Big Data. The algorithm exploits all hashtags and emoticons inside a tweet, as sentiment labels, and proceeds to a classification method of diverse sentiment types in a parallel and distributed manner. Moreover, the sentiment analysis tool is based on Machine Learning methodologies alongside Natural Language Processing techniques and utilizes Apache Spark’s Machine learning library, MLlib. In order to address the nature of Big Data, we introduce some pre-processing steps for achieving better results in Sentiment Analysis as well as Bloom filters to compact the storage size of intermediate data and boost the performance of our algorithm. Finally, the proposed system was trained and validated with real data crawled by Twitter, and, through an extensive experimental evaluation, we prove that our solution is efficient, robust and scalable while confirming the quality of our sentiment identification.

  11. Deep Learning for Sentiment Analysis : A Survey

    OpenAIRE

    Zhang, Lei; Wang, Shuai; Liu, Bing

    2018-01-01

    Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state-of-the-art prediction results. Along with the success of deep learning in many other application domains, deep learning is also popularly used in sentiment analysis in recent years. This paper first gives an overview of deep learning and then provides a comprehensive survey of its current applications in sentiment analysis.

  12. News media and investor sentiment over the long run

    OpenAIRE

    Hanna, Alan J.; Turner, John D.; Walker, Clive B.

    2017-01-01

    This paper studies the effect of investor sentiment on the London stock market on a daily basis over the period 1899 to 2010. We use a broad mix of reporting from the Financial Times as our proxy for investor sentiment. The main contribution of this paper is threefold. First, newspaper commentary, which was sentiment-laden, but information-light, in the Financial Times affects returns. Second, we find evidence that sentiment plays a role in propagating price movements, particularly during bul...

  13. Unsupervised and knowledge-poor approaches to sentiment analysis

    OpenAIRE

    Zagibalov, Taras

    2010-01-01

    Sentiment analysis focuses upon automatic classiffication of a document's sentiment (and more generally extraction of opinion from text). Ways of expressing sentiment have been\\ud shown to be dependent on what a document is about (domain-dependency). This complicates supervised methods for sentiment analysis which rely on extensive use of training data or linguistic resources that are usually either domain-specific or generic. Both kinds of resources prevent classiffiers from performing well ...

  14. A global optimization approach to multi-polarity sentiment analysis.

    Science.gov (United States)

    Li, Xinmiao; Li, Jing; Wu, Yukeng

    2015-01-01

    Following the rapid development of social media, sentiment analysis has become an important social media mining technique. The performance of automatic sentiment analysis primarily depends on feature selection and sentiment classification. While information gain (IG) and support vector machines (SVM) are two important techniques, few studies have optimized both approaches in sentiment analysis. The effectiveness of applying a global optimization approach to sentiment analysis remains unclear. We propose a global optimization-based sentiment analysis (PSOGO-Senti) approach to improve sentiment analysis with IG for feature selection and SVM as the learning engine. The PSOGO-Senti approach utilizes a particle swarm optimization algorithm to obtain a global optimal combination of feature dimensions and parameters in the SVM. We evaluate the PSOGO-Senti model on two datasets from different fields. The experimental results showed that the PSOGO-Senti model can improve binary and multi-polarity Chinese sentiment analysis. We compared the optimal feature subset selected by PSOGO-Senti with the features in the sentiment dictionary. The results of this comparison indicated that PSOGO-Senti can effectively remove redundant and noisy features and can select a domain-specific feature subset with a higher-explanatory power for a particular sentiment analysis task. The experimental results showed that the PSOGO-Senti approach is effective and robust for sentiment analysis tasks in different domains. By comparing the improvements of two-polarity, three-polarity and five-polarity sentiment analysis results, we found that the five-polarity sentiment analysis delivered the largest improvement. The improvement of the two-polarity sentiment analysis was the smallest. We conclude that the PSOGO-Senti achieves higher improvement for a more complicated sentiment analysis task. We also compared the results of PSOGO-Senti with those of the genetic algorithm (GA) and grid search method. From

  15. Self-training from labeled features for sentiment analysis

    OpenAIRE

    He, Yulan; Zhou, Deyu

    2011-01-01

    Sentiment analysis concerns about automatically identifying sentiment or opinion expressed in a given piece of text. Most prior work either use prior lexical knowledge defined as sentiment polarity of words or view the task as a text classification problem and rely on labeled corpora to train a sentiment classifier. While lexicon-based approaches do not adapt well to different domains, corpus-based approaches require expensive manual annotation effort. In this paper, we propose a novel framew...

  16. Sentence-based sentiment analysis with domain adaptation capability

    OpenAIRE

    Gezici, Gizem

    2013-01-01

    Sentiment analysis aims to automatically estimate the sentiment in a given text as positive, objective or negative, possibly together with the strength of the sentiment. Polarity lexicons that indicate how positive or negative each term is, are often used as the basis of many sentiment analysis approaches. Domain-specific polarity lexicons are expensive and time-consuming to build; hence, researchers often use a general purpose or domainindependent lexicon as the basis of their analysis. In t...

  17. 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.

  18. Assessing Anti-American Sentiment Through Social Media Analysis

    Science.gov (United States)

    2016-12-01

    americas-image/pg-2014-07-14- balance-of-power-1-02/. 11 Saeed, Ahsan. "Twitter Landscape Of Pakistan – First Edition." Twittistaan. Last modified...February 5, 2014. http://twittistaan.com/digital-media/infographics/twitter- landscape -of-pakistan-first-edition/. 12 “Pakistan Needs to Tweet More,” DAWN...Ibid., 5. 11 Americanism is unique, as they look at editorial cartoons in both English and Spanish and analyze the sentiment under a statistical lens

  19. Sentiment analysis of Chinese microblogging based on sentiment ontology: a case study of `7.23 Wenzhou Train Collision'

    Science.gov (United States)

    Shi, Wei; Wang, Hongwei; He, Shaoyi

    2013-12-01

    Sentiment analysis of microblogging texts can facilitate both organisations' public opinion monitoring and governments' response strategies development. Nevertheless, most of the existing analysis methods are conducted on Twitter, lacking of sentiment analysis of Chinese microblogging (Weibo), and they generally rely on a large number of manually annotated training or machine learning to perform sentiment classification, yielding with difficulties in application. This paper addresses these problems and employs a sentiment ontology model to examine sentiment analysis of Chinese microblogging. We conduct a sentiment analysis of all public microblogging posts about '7.23 Wenzhou Train Collision' broadcasted by Sina microblogging users between 23 July and 1 August 2011. For every day in this time period, we first extract eight dimensions of sentiment (expect, joy, love, surprise, anxiety, sorrow, angry, and hate), and then build fuzzy sentiment ontology based on HowNet and semantic similarity for sentiment analysis; we also establish computing methods of influence and sentiment of microblogging texts; and we finally explore the change of public sentiment after '7.23 Wenzhou Train Collision'. The results show that the established sentiment analysis method has excellent application, and the change of different emotional values can reflect the success or failure of guiding the public opinion by the government.

  20. Sentiment classification with interpolated information diffusion kernels

    NARCIS (Netherlands)

    Raaijmakers, S.

    2007-01-01

    Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of

  1. Sentiment Analysis for Exploratory Data Analysis

    Directory of Open Access Journals (Sweden)

    Zoë Wilkinson Saldaña

    2018-01-01

    Full Text Available In this lesson you will learn to conduct 'sentiment analysis' on texts and to interpret the results. This is a form of exploratory data analysis based on natural language processing. You will learn to install all appropriate software and to build a reusable program that can be applied to your own texts.

  2. 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.

  3. Twitter sentiment around the Earnings Announcement events.

    Science.gov (United States)

    Gabrovšek, Peter; Aleksovski, Darko; Mozetič, Igor; Grčar, Miha

    2017-01-01

    We investigate the relationship between social media, Twitter in particular, and stock market. We provide an in-depth analysis of the Twitter volume and sentiment about the 30 companies in the Dow Jones Industrial Average index, over a period of three years. We focus on Earnings Announcements and show that there is a considerable difference with respect to when the announcements are made: before the market opens or after the market closes. The two different timings of the Earnings Announcements were already investigated in the financial literature, but not yet in the social media. We analyze the differences in terms of the Twitter volumes, cumulative abnormal returns, trade returns, and earnings surprises. We report mixed results. On the one hand, we show that the Twitter sentiment (the collective opinion of the users) on the day of the announcement very well reflects the stock moves on the same day. We demonstrate this by applying the event study methodology, where the polarity of the Earnings Announcements is computed from the Twitter sentiment. Cumulative abnormal returns are high (2-4%) and statistically significant. On the other hand, we find only weak predictive power of the Twitter sentiment one day in advance. It turns out that it is important how to account for the announcements made after the market closes. These after-hours announcements draw high Twitter activity immediately, but volume and price changes in trading are observed only on the next day. On the day before the announcements, the Twitter volume is low, and the sentiment has very weak predictive power. A useful lesson learned is the importance of the proper alignment between the announcements, trading and Twitter data.

  4. 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...

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  11. 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.

  12. Classifying sentiment in microblogs: is brevity an advantage?

    OpenAIRE

    Bermingham, Adam; Smeaton, Alan F.

    2010-01-01

    Microblogs as a new textual domain offer a unique proposition for sentiment analysis. Their short document length suggests any sentiment they contain is compact and explicit. However, this short length coupled with their noisy nature can pose difficulties for standard machine learning document representations. In this work we examine the hypothesis that it is easier to classify the sentiment in these short form documents than in longer form documents. Surprisingly, we find classifying sentime...

  13. Sentiment analysis in medical settings: New opportunities and challenges.

    Science.gov (United States)

    Denecke, Kerstin; Deng, Yihan

    2015-05-01

    Clinical documents reflect a patient's health status in terms of observations and contain objective information such as descriptions of examination results, diagnoses and interventions. To evaluate this information properly, assessing positive or negative clinical outcomes or judging the impact of a medical condition on patient's well being are essential. Although methods of sentiment analysis have been developed to address these tasks, they have not yet found broad application in the medical domain. In this work, we characterize the facets of sentiment in the medical sphere and identify potential use cases. Through a literature review, we summarize the state of the art in healthcare settings. To determine the linguistic peculiarities of sentiment in medical texts and to collect open research questions of sentiment analysis in medicine, we perform a quantitative assessment with respect to word usage and sentiment distribution of a dataset of clinical narratives and medical social media derived from six different sources. Word usage in clinical narratives differs from that in medical social media: Nouns predominate. Even though adjectives are also frequently used, they mainly describe body locations. Between 12% and 15% of sentiment terms are determined in medical social media datasets when applying existing sentiment lexicons. In contrast, in clinical narratives only between 5% and 11% opinionated terms were identified. This proves the less subjective use of language in clinical narratives, requiring adaptations to existing methods for sentiment analysis. Medical sentiment concerns the patient's health status, medical conditions and treatment. Its analysis and extraction from texts has multiple applications, even for clinical narratives that remained so far unconsidered. Given the varying usage and meanings of terms, sentiment analysis from medical documents requires a domain-specific sentiment source and complementary context-dependent features to be able to

  14. Sentiment Analysis Using Common-Sense and Context Information

    OpenAIRE

    Agarwal, Basant; Mittal, Namita; Bansal, Pooja; Garg, Sonal

    2015-01-01

    Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific conc...

  15. Enhancing Domain Specific Sentiment Lexicon for Issue Identification

    OpenAIRE

    N, Madhusudanan; Gurumoorthy, B.; Chakrabarti, Amaresh

    2016-01-01

    Part 1: Knowledge Sharing, Re-use and Preservation; International audience; The research work reported here is part of a larger project aimed at acquiring knowledge about issues in assembly, from documents. In order to do so, the first step is to identify the presence of issues. For this, sentiment analysis is proposed as a means. The presence of issues is proposed to be found by detecting negative sentiment. However, general English sentiment lexicons are not enough to detect negative sentim...

  16. 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

  17. Sentiment Perception of Readers and Writers in Emoji use

    OpenAIRE

    Berengueres, Jose; Castro, Dani

    2017-01-01

    Previous research has traditionally analyzed emoji sentiment from the point of view of the reader of the content not the author. Here, we analyze emoji sentiment from the point of view of the author and present a emoji sentiment benchmark that was built from an employee happiness dataset where emoji happen to be annotated with daily happiness of the author of the comment. The data spans over 3 years, and 4k employees of 56 companies based in Barcelona. We compare sentiment of writers to reade...

  18. A global optimization approach to multi-polarity sentiment analysis.

    Directory of Open Access Journals (Sweden)

    Xinmiao Li

    Full Text Available Following the rapid development of social media, sentiment analysis has become an important social media mining technique. The performance of automatic sentiment analysis primarily depends on feature selection and sentiment classification. While information gain (IG and support vector machines (SVM are two important techniques, few studies have optimized both approaches in sentiment analysis. The effectiveness of applying a global optimization approach to sentiment analysis remains unclear. We propose a global optimization-based sentiment analysis (PSOGO-Senti approach to improve sentiment analysis with IG for feature selection and SVM as the learning engine. The PSOGO-Senti approach utilizes a particle swarm optimization algorithm to obtain a global optimal combination of feature dimensions and parameters in the SVM. We evaluate the PSOGO-Senti model on two datasets from different fields. The experimental results showed that the PSOGO-Senti model can improve binary and multi-polarity Chinese sentiment analysis. We compared the optimal feature subset selected by PSOGO-Senti with the features in the sentiment dictionary. The results of this comparison indicated that PSOGO-Senti can effectively remove redundant and noisy features and can select a domain-specific feature subset with a higher-explanatory power for a particular sentiment analysis task. The experimental results showed that the PSOGO-Senti approach is effective and robust for sentiment analysis tasks in different domains. By comparing the improvements of two-polarity, three-polarity and five-polarity sentiment analysis results, we found that the five-polarity sentiment analysis delivered the largest improvement. The improvement of the two-polarity sentiment analysis was the smallest. We conclude that the PSOGO-Senti achieves higher improvement for a more complicated sentiment analysis task. We also compared the results of PSOGO-Senti with those of the genetic algorithm (GA and grid

  19. 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%.

  20. Measuring Corporate Reputation using Sentiment Analysis

    DEFF Research Database (Denmark)

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

    In recent years, new digital media have become important for social networking and content sharing. Due to their large diffusion, social media platforms have also both increased the strategic importance of managing corporate reputation and rendered this more difficult. Companies are increasingly...... 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...... the real time evolution of company reputation....

  1. Sentiment Polarization and Balance among Users in Online Social Networks

    DEFF Research Database (Denmark)

    Hillmann, Robert; Trier, Matthias

    2012-01-01

    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...

  2. 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.

  3. Machine Learning-Based Sentimental Analysis for Twitter Accounts

    Directory of Open Access Journals (Sweden)

    Ali Hasan

    2018-02-01

    Full Text Available Growth in the area of opinion mining and sentiment analysis has been rapid and aims to explore the opinions or text present on different platforms of social media through machine-learning techniques with sentiment, subjectivity analysis or polarity calculations. Despite the use of various machine-learning techniques and tools for sentiment analysis during elections, there is a dire need for a state-of-the-art approach. To deal with these challenges, the contribution of this paper includes the adoption of a hybrid approach that involves a sentiment analyzer that includes machine learning. Moreover, this paper also provides a comparison of techniques of sentiment analysis in the analysis of political views by applying supervised machine-learning algorithms such as Naïve Bayes and support vector machines (SVM.

  4. 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.

  5. Does sustained participation in an online health community affect sentiment?

    Science.gov (United States)

    Zhang, Shaodian; Bantum, Erin; Owen, Jason; Elhadad, Noémie

    2014-01-01

    A large number of patients rely on online health communities to exchange information and psychosocial support with their peers. Examining participation in a community and its impact on members' behaviors and attitudes is one of the key open research questions in the field of study of online health communities. In this paper, we focus on a large public breast cancer community and conduct sentiment analysis on all its posts. We investigate the impact of different factors on post sentiment, such as time since joining the community, posting activity, age of members, and cancer stage of members. We find that there is a significant increase in sentiment of posts through time, with different patterns of sentiment trends for initial posts in threads and reply posts. Factors each play a role; for instance stage-IV members form a particular sub-community with patterns of sentiment and usage distinct from others members.

  6. Anti-globalization Actions – a Risk for Public Order and Safety

    Directory of Open Access Journals (Sweden)

    Cristian GISCA

    2010-09-01

    Full Text Available As a process, globalization has a long history. Some sustain that the current phase of globalization has nothing new, since its rise the capitalism was a transnational phenomenon. What is new, in the recent decades, is the amazing revolution of information and communication technology, which generated a qualitative and quantitative study of globalization process, especially on itseconomic dimension. On one hand, the process creates transnational networks, including people networks, and on the other hand it excludes and atomizes large human communities, triggering movements, hence the anti-globalization action.

  7. 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.

  8. Sentiment Knowledge Discovery in Twitter Streaming Data

    Science.gov (United States)

    Bifet, Albert; Frank, Eibe

    Micro-blogs are a challenging new source of information for data mining techniques. Twitter is a micro-blogging service built to discover what is happening at any moment in time, anywhere in the world. Twitter messages are short, and generated constantly, and well suited for knowledge discovery using data stream mining. We briefly discuss the challenges that Twitter data streams pose, focusing on classification problems, and then consider these streams for opinion mining and sentiment analysis. To deal with streaming unbalanced classes, we propose a sliding window Kappa statistic for evaluation in time-changing data streams. Using this statistic we perform a study on Twitter data using learning algorithms for data streams.

  9. 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......, and can serve as a basis for communication design choices that support strategic relationship goals for organizations....

  10. 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.

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

    OpenAIRE

    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 th...

  12. Modelling SO-CAL in an Inheritance-based Sentiment Analysis Framework

    OpenAIRE

    Satthar, F. Sharmila

    2015-01-01

    Sentiment analysis is the computational study of people's opinions, as expressed in text. This is an active area of research in Natural Language Processing with many applications in social media. There are two main approaches to sentiment analysis: machine learning and lexicon-based. The machine learning approach uses statistical modelling techniques, whereas the lexicon-based approach uses 'sentiment lexicons' containing explicit sentiment values for individual words to calculate sentiment s...

  13. 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.

  14. Sentiment Classification of Reviews Using SentiWordNet

    OpenAIRE

    Ohana, Bruno; Tierney, Brendan

    2009-01-01

    Sentiment classification concerns the use of automatic methods for predicting the orientation of subjective content on text documents, with applications on a number of areas including recommender and advertising systems, customer intelligence and information retrieval. SentiWordNet is an opinion lexicon derived from the WordNet database where each term is associated with numerical scores indicating positive and negative sentiment information. This research presents the results of applying the...

  15. 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...... methods for sentiment analysis, which often work on sentence or word level, and are argued to have difficulties in capturing long distance dependencies....

  16. Sentiment Prediction Based on Dempster-Shafer Theory of Evidence

    OpenAIRE

    Mohammad Ehsan Basiri; Ahmad Reza Naghsh-Nilchi; Nasser Ghasem-Aghaee

    2014-01-01

    Sentiment prediction techniques are often used to assign numerical scores to free-text format reviews written by people in online review websites. In order to exploit the fine-grained structural information of textual content, a review may be considered as a collection of sentences, each with its own sentiment orientation and score. In this manner, a score aggregation method is needed to combine sentence-level scores into an overall review rating. While recent work has concentrated on designi...

  17. Selling Sentiment: The Commodification of Emotion in Victorian Visual Culture

    Directory of Open Access Journals (Sweden)

    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.

  18. THE EFFECT OF INVESTOR SENTIMENT ON ISE SECTOR INDICES

    Directory of Open Access Journals (Sweden)

    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.

  19. 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

  20. 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…

  1. Strength in Numbers: Using Big Data to Simplify Sentiment Classification.

    Science.gov (United States)

    Filippas, Apostolos; Lappas, Theodoros

    2017-09-01

    Sentiment classification, the task of assigning a positive or negative label to a text segment, is a key component of mainstream applications such as reputation monitoring, sentiment summarization, and item recommendation. Even though the performance of sentiment classification methods has steadily improved over time, their ever-increasing complexity renders them comprehensible by only a shrinking minority of expert practitioners. For all others, such highly complex methods are black-box predictors that are hard to tune and even harder to justify to decision makers. Motivated by these shortcomings, we introduce BigCounter: a new algorithm for sentiment classification that substitutes algorithmic complexity with Big Data. Our algorithm combines standard data structures with statistical testing to deliver accurate and interpretable predictions. It is also parameter free and suitable for use virtually "out of the box," which makes it appealing for organizations wanting to leverage their troves of unstructured data without incurring the significant expense of creating in-house teams of data scientists. Finally, BigCounter's efficient and parallelizable design makes it applicable to very large data sets. We apply our method on such data sets toward a study on the limits of Big Data for sentiment classification. Our study finds that, after a certain point, predictive performance tends to converge and additional data have little benefit. Our algorithmic design and findings provide the foundations for future research on the data-over-computation paradigm for classification problems.

  2. Sentiment analysis of Arabic tweets using text mining techniques

    Science.gov (United States)

    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.

  3. 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.

  4. Sentiment analysis using common-sense and context information.

    Science.gov (United States)

    Agarwal, Basant; Mittal, Namita; Bansal, Pooja; Garg, Sonal

    2015-01-01

    Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods.

  5. Sentiment Analysis Using Common-Sense and Context Information

    Directory of Open Access Journals (Sweden)

    Basant Agarwal

    2015-01-01

    Full Text Available Sentiment analysis research has been increasing tremendously in recent times due to the wide range of business and social applications. Sentiment analysis from unstructured natural language text has recently received considerable attention from the research community. In this paper, we propose a novel sentiment analysis model based on common-sense knowledge extracted from ConceptNet based ontology and context information. ConceptNet based ontology is used to determine the domain specific concepts which in turn produced the domain specific important features. Further, the polarities of the extracted concepts are determined using the contextual polarity lexicon which we developed by considering the context information of a word. Finally, semantic orientations of domain specific features of the review document are aggregated based on the importance of a feature with respect to the domain. The importance of the feature is determined by the depth of the feature in the ontology. Experimental results show the effectiveness of the proposed methods.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. Framing Collective Action Against Neoliberalism: The Case of the “Anti-Globalization” Movement

    Directory of Open Access Journals (Sweden)

    Jeffrey M. Ayres

    2015-08-01

    Full Text Available The rise of the protest movement against neoliberal globalization represents one of the most signi?cant illustrations of social con?ict and contentious political behavior of the past several decades. This paper contends that central to the movement’s rise and evolution has been the active mobilization of meanings or interpretations critical of neoliberal policies and institutions. In e?ect, the so-called “anti-globalization movement” has bene?ted particularly from a transnationally-shared diagnosis, which implicates neoliberalism for a host of global social ills. However, civil society activists, especially after the Seattle World Trade Organization protests in 1999, have had a dif?cult time generating agreed upon strategic responses to neoliberal policies. In particular, the political environment for frame dissemination has become a much more contested one in the aftermath of the September 11 terrorist attacks on the United States, as regional and tactical di?erences within the protest move-ment have become much more apparent. The di?cult experiences of civil society groups committed to sustaining protest against neo-liberal globalization are not unusual, but consistent with the history of other protest movements. These movements similarly matured and positioned themselves as genuine forces for substantial political and social change.

  8. Enhancing the Sentiment Classification Accuracy of Twitter Data using Machine Learning Algorithms

    OpenAIRE

    Muthukumar Bhuvaneswari1; Vasudevan Srividhya2

    2017-01-01

    Sentiment analysis or opinion mining is the study of public opinions, sentiments, attitudes, and emotions expressed in social media. This is one of the most dynamic research areas in natural language processing and text mining in current years. It is a domain that involves the finding of user sentiment, emotion and opinion within natural language text. The growing significance of sentiment analysis coincides with the increase of social media such as reviews, forum discussions, blogs, micro-bl...

  9. Sentiment analysis using domain-adaptation and sentence-based analysis

    OpenAIRE

    Gezici, Gizem; Yanıkoğlu, Berrin; Yanikoglu, Berrin; Tapucu, Dilek; Saygın, Yücel; Saygin, Yucel

    2015-01-01

    Sentiment analysis aims to automatically estimate the sentiment in a given text as positive, objective or negative, possibly together with the strength of the sentiment. Polarity lexicons that indicate how positive or negative each term is, are often used as the basis of many sentiment analysis approaches. Domain-specific polarity lexicons are expensive and time-consuming to build; hence, researchers often use a general purpose or domain-independent lexicon as the basis of their analysis. ...

  10. Assessing Sentiment In Conflict Zones Through Social Media

    Science.gov (United States)

    2016-12-01

    Strategic Studies 27, no. 1 (2004): 35–58; Frank Hoffman , “Hybrid Warfare and Challenges,” JFQ 52, no. 1 (2009); James Clancy and Chuck Crossett...Science and Technology 63, no. 12 (2012): 2521–2535; Albert Bifet and Eibe Frank, “Sentiment Knowledge Discovery in Twitter Streaming Data,” in DS’10...Thousand Oaks, CA: SAGE Publications, 2013. Bifet, Albert , and Eibe Frank. “Sentiment Knowledge Discovery in Twitter Streaming Data.” In DS’10

  11. 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

  12. 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...

  13. Sentiments analysis at conceptual level making use of the Narrative Knowledge Representation Language.

    Science.gov (United States)

    Zarri, Gian Piero

    2014-10-01

    This paper illustrates some of the knowledge representation structures and inference procedures proper to a high-level, fully implemented conceptual language, NKRL (Narrative Knowledge Representation Language). The aim is to show how these tools can be used to deal, in a sentiment analysis/opinion mining context, with some common types of human (and non-human) "behaviors". These behaviors correspond, in particular, to the concrete, mutual relationships among human and non-human characters that can be expressed under the form of non-fictional and real-time "narratives" (i.e., as logically and temporally structured sequences of "elementary events"). Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. 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.

  15. 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…

  16. 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...

  17. 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’

  18. 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.

  19. Sentiments Analysis of Reviews Based on ARCNN Model

    Science.gov (United States)

    Xu, Xiaoyu; Xu, Ming; Xu, Jian; Zheng, Ning; Yang, Tao

    2017-10-01

    The sentiments analysis of product reviews is designed to help customers understand the status of the product. The traditional method of sentiments analysis relies on the input of a fixed feature vector which is performance bottleneck of the basic codec architecture. In this paper, we propose an attention mechanism with BRNN-CNN model, referring to as ARCNN model. In order to have a good analysis of the semantic relations between words and solves the problem of dimension disaster, we use the GloVe algorithm to train the vector representations for words. Then, ARCNN model is proposed to deal with the problem of deep features training. Specifically, BRNN model is proposed to investigate non-fixed-length vectors and keep time series information perfectly and CNN can study more connection of deep semantic links. Moreover, the attention mechanism can automatically learn from the data and optimize the allocation of weights. Finally, a softmax classifier is designed to complete the sentiment classification of reviews. Experiments show that the proposed method can improve the accuracy of sentiment classification compared with benchmark methods.

  20. Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability

    DEFF Research Database (Denmark)

    Rombouts, Jerome V.K.; Stentoft, Lars; Violante, Francesco

    and realized variances, our model allows to infer the occurrence and size of extreme variance events, and construct indicators signalling agents sentiment towards future market conditions. Our results show that excess returns are to a large extent explained by fear or optimism towards future extreme variance...

  1. 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.

  2. 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

  3. 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.

  4. An unsupervised aspect detection model for sentiment analysis of reviews

    NARCIS (Netherlands)

    Bagheri, Ayoub; Saraee, M.; de Jong, Franciska M.G.

    With the rapid growth of user-generated content on the internet, sentiment analysis of online reviews has become a hot research topic recently, but due to variety and wide range of products and services, the supervised and domain-specific models are often not practical. As the number of reviews

  5. 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.

  6. 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.

  7. Sentiment Analysis and Social Cognition Engine (SEANCE): An automatic tool for sentiment, social cognition, and social-order analysis.

    Science.gov (United States)

    Crossley, Scott A; Kyle, Kristopher; McNamara, Danielle S

    2017-06-01

    This study introduces the Sentiment Analysis and Cognition Engine (SEANCE), a freely available text analysis tool that is easy to use, works on most operating systems (Windows, Mac, Linux), is housed on a user's hard drive (as compared to being accessed via an Internet interface), allows for batch processing of text files, includes negation and part-of-speech (POS) features, and reports on thousands of lexical categories and 20 component scores related to sentiment, social cognition, and social order. In the study, we validated SEANCE by investigating whether its indices and related component scores can be used to classify positive and negative reviews in two well-known sentiment analysis test corpora. We contrasted the results of SEANCE with those from Linguistic Inquiry and Word Count (LIWC), a similar tool that is popular in sentiment analysis, but is pay-to-use and does not include negation or POS features. The results demonstrated that both the SEANCE indices and component scores outperformed LIWC on the categorization tasks.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. 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

  10. 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

  11. A hybrid approach to sentiment sentence classification in suicide notes.

    Science.gov (United States)

    Sohn, Sunghwan; Torii, Manabu; Li, Dingcheng; Wagholikar, Kavishwar; Wu, Stephen; Liu, Hongfang

    2012-01-01

    This paper describes the sentiment classification system developed by the Mayo Clinic team for the 2011 I2B2/VA/Cincinnati Natural Language Processing (NLP) Challenge. The sentiment classification task is to assign any pertinent emotion to each sentence in suicide notes. We have implemented three systems that have been trained on suicide notes provided by the I2B2 challenge organizer-a machine learning system, a rule-based system, and a system consisting of a combination of both. Our machine learning system was trained on re-annotated data in which apparently inconsistent emotion assignment was adjusted. Then, the machine learning methods by RIPPER and multinomial Naïve Bayes classifiers, manual pattern matching rules, and the combination of the two systems were tested to determine the emotions within sentences. The combination of the machine learning and rule-based system performed best and produced a micro-average F-score of 0.5640.

  12. 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.

  13. 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.

  14. 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...

  15. Automatic Expansion of a Social Judgment Lexicon for Sentiment Analysis

    OpenAIRE

    Silva, Mário J.; Carvalho, Paula; Costa, Carlos; Sarmento, Luís

    2010-01-01

    Reviewed by Francisco Couto We present a new method for automatically enlarging a sentiment lexicon for mining social judgments from text, i.e., extracting opinions about human subjects. We use a two-step approach: first, we find which adjectives can be used as human modifiers, and then we assign their polarity attribute. To identify the human modifiers, we developed a set of hand-crafted lexico-syntactic rules representing elementary copular and adnominal constructions where such predicat...

  16. Presidential rhetoric, sentiment and their relation to stock markets

    OpenAIRE

    Partelová, Mária

    2017-01-01

    This thesis intends to uncover the linkages between the emotions contained within remarks of the president of the United States expressed on Twitter and movements of the stock market indices. The daily comments of the two consecutive presidents, Barack Obama and Donald Trump are annotated with sentiment intensity values using the lexicon-based model called VADER. Our analysis further focuses on testing for Granger causality using the bivariate vector autoregression. Overall, three major stock...

  17. 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.

  18. Linked-data based domain-specific sentiment lexicons

    OpenAIRE

    Vulcu, Gabriela; Lario Monje, Raúl; Muñoz, Mario; Buitelaar, Paul; Iglesias Fernandez, Carlos Angel

    2014-01-01

    In this paper we present a dataset componsed of domain-specific sentiment lexicons in six languages for two domains. We used existing collections of reviews from Trip Advisor, Amazon, the Stanford Network Analysis Project and the OpinRank Review Dataset. We use an RDF model based on the lemon and Marl formats to represent the lexicons. We describe the methodology that we applied to generate the domain-specific lexicons and we provide access information to our datasets.

  19. 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.

  20. 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.

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

    DEFF Research Database (Denmark)

    Nielsen, Finn Årup

    2011-01-01

    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......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...... 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....

  2. Visual and Textual Sentiment Analysis of a Microblog Using Deep Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Yuhai Yu

    2016-06-01

    Full Text Available Sentiment analysis of online social media has attracted significant interest recently. Many studies have been performed, but most existing methods focus on either only textual content or only visual content. In this paper, we utilize deep learning models in a convolutional neural network (CNN to analyze the sentiment in Chinese microblogs from both textual and visual content. We first train a CNN on top of pre-trained word vectors for textual sentiment analysis and employ a deep convolutional neural network (DNN with generalized dropout for visual sentiment analysis. We then evaluate our sentiment prediction framework on a dataset collected from a famous Chinese social media network (Sina Weibo that includes text and related images and demonstrate state-of-the-art results on this Chinese sentiment analysis benchmark.

  3. 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.

  4. Investor sentiment, optimism and excess stock market returns. Evidence from emerging markets

    OpenAIRE

    Karolina Daszynska-Zygadlo; Aleksandra Szpulak; Adam Szyszka

    2014-01-01

    We test the existence of a contemporaneous relationship between sentiment/optimism indexes and returns at the aggregate market level in eight emerging markets, namely: Brazil, China, India, Mexico, Poland, Republic of South Africa, Russia and Turkey. We use sentiment and optimism Thomson Reuters MarketPsych Indexes that are based on scanning media coverage for relevant text reflecting particular moods and opinions. We find that there is a positive relationship between investor sentiment index...

  5. 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...

  6. Video (GIF) Sentiment Analysis using Large-Scale Mid-Level Ontology

    OpenAIRE

    Cai, Zheng; Cao, Donglin; Ji, Rongrong

    2015-01-01

    With faster connection speed, Internet users are now making social network a huge reservoir of texts, images and video clips (GIF). Sentiment analysis for such online platform can be used to predict political elections, evaluates economic indicators and so on. However, GIF sentiment analysis is quite challenging, not only because it hinges on spatio-temporal visual contentabstraction, but also for the relationship between such abstraction and final sentiment remains unknown.In this paper, we ...

  7. Twitter Sentiment Analysis: Lexicon Method, Machine Learning Method and Their Combination

    OpenAIRE

    Kolchyna, Olga; Souza, Tharsis T. P.; Treleaven, Philip; Aste, Tomaso

    2015-01-01

    This paper covers the two approaches for sentiment analysis: i) lexicon based method; ii) machine learning method. We describe several techniques to implement these approaches and discuss how they can be adopted for sentiment classification of Twitter messages. We present a comparative study of different lexicon combinations and show that enhancing sentiment lexicons with emoticons, abbreviations and social-media slang expressions increases the accuracy of lexicon-based classification for Twi...

  8. Domain-Specific Sentiment Word Extraction by Seed Expansion and Pattern Generation

    OpenAIRE

    Duyu, Tang; Bing, Qin; LanJun, Zhou; KamFai, Wong; Yanyan, Zhao; Ting, Liu

    2013-01-01

    This paper focuses on the automatic extraction of domain-specific sentiment word (DSSW), which is a fundamental subtask of sentiment analysis. Most previous work utilizes manual patterns for this task. However, the performance of those methods highly relies on the labelled patterns or selected seeds. In order to overcome the above problem, this paper presents an automatic framework to detect large-scale domain-specific patterns for DSSW extraction. To this end, sentiment seeds are extracted f...

  9. Non-domain specific and translated sentiment analysis - Local lexical analyzer

    OpenAIRE

    Olsen, Erik Kringstad

    2015-01-01

    There is an ever-growing amount of opinionated data available on the Web, in form of reviews, discussions and blogs. This data can potentially provide a lot of information through sentiment analysis and data mining in general. However, most research in the field of sentiment analysis has been locked to a single language and a single domain. Thus, the main objective of this thesis is to answer the question: How can a sentiment analysis tool that is independent...

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

    Directory of Open Access Journals (Sweden)

    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.

  11. 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

  12. Influence and Dissemination Of Sentiments in Social Network Communication Patterns

    DEFF Research Database (Denmark)

    Hillmann, Robert; Trier, Matthias

    2013-01-01

    in online environments. We develop a theoretical framework that tries to bridge the gap between social influence theories that focus on offline interactions on one hand and online interaction in social networks on the other hand. We then test our hypothesis about the influence and dissemination...... 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....

  13. 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 agents and sentiment in the heterogeneous agent model.pdf

  14. Using Social Media Sentiment Analysis to Understand Audiences

    DEFF Research Database (Denmark)

    McGuire, Mark; Kampf, Constance Elizabeth

    2015-01-01

    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......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...

  15. The expression of sentiment in user reviews of hotels

    OpenAIRE

    Moreno-Ortiz, Antonio; Fuster-Márquez, Miguel

    2017-01-01

    The linguistic expression of sentiment, understood as the polarity of an opinion, is known to be domain-specific to a certain extent (Aue & Gamon, 2005; Choi et al., 2009). Even though many words and expressions convey the same evaluation across domains (e.g., “excellent”, “terrible”), many others acquire a more precise semantic orientation within a specific domain. For example, features such as size or location (and the lexical expressions that are used to express them) may or may not convey...

  16. Financial News and Market Panics in the Age of Highfrequency Sentiment Trading Algorithms

    DEFF Research Database (Denmark)

    Kleinnijenhuis, Jan; Schultz, Friederike; Oegema, Dirk

    2013-01-01

    Whether financial news may contribute to market panics is not an innocent question. A positive answer is easily used as a legitimation to limit the freedom of financial journalists. Long-term effects of news are moreover inconsistent with the Efficient Market Hypothesis (EMH), which maintains...... that new information gives immediately rise to a new equilibrium. The EMH is under discussion, however, as a result of the transformation of financial markets and of financial journalism due to new economic thoughts, new communication theories, high-frequency trading and high-frequency sentiment analysis....... As a case study of a market panic we show the impact of US news, UK news and Dutch news on three Dutch banks during the financial crisis of 2007–9. To avoid market panics, financial journalists may strive for greater transparency, not only on asset prices and corporate philosophies, but also on network...

  17. 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...... examined the existence or distribution of sentiments in online communication at a general level or in small observed groups....

  18. 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

  19. Trauma, Justice and the Politics of Emotion: The Violence of Sentimentality in Education

    Science.gov (United States)

    Zembylas, Michalinos

    2008-01-01

    This article interrogates the sentimentality, resentment or desensitization in education as a result of the politics of emotion in the circulation of trauma narratives. Such an interrogation advises a different analysis of trauma narratives, one that acknowledges the politics of trauma and the dangers from its rhetoric. Sentimental education takes…

  20. 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…

  1. 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

  2. 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

  3. 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

  4. 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…

  5. A Multilayer Naïve Bayes Model for Analyzing User’s Retweeting Sentiment Tendency

    Directory of Open Access Journals (Sweden)

    Mengmeng Wang

    2015-01-01

    Full Text Available Today microblogging has increasingly become a means of information diffusion via user’s retweeting behavior. Since retweeting content, as context information of microblogging, is an understanding of microblogging, hence, user’s retweeting sentiment tendency analysis has gradually become a hot research topic. Targeted at online microblogging, a dynamic social network, we investigate how to exploit dynamic retweeting sentiment features in retweeting sentiment tendency analysis. On the basis of time series of user’s network structure information and published text information, we first model dynamic retweeting sentiment features. Then we build Naïve Bayes models from profile-, relationship-, and emotion-based dimensions, respectively. Finally, we build a multilayer Naïve Bayes model based on multidimensional Naïve Bayes models to analyze user’s retweeting sentiment tendency towards a microblog. Experiments on real-world dataset demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of dynamic retweeting sentiment features and temporal information in retweeting sentiment tendency analysis. What is more, we provide a new train of thought for retweeting sentiment tendency analysis in dynamic social networks.

  6. 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

  7. 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.

  8. 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.

  9. 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.

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

    Science.gov (United States)

    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.

  11. 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.

  12. 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.

  13. Feature-level sentiment analysis by using comparative domain corpora

    Science.gov (United States)

    Quan, Changqin; Ren, Fuji

    2016-06-01

    Feature-level sentiment analysis (SA) is able to provide more fine-grained SA on certain opinion targets and has a wider range of applications on E-business. This study proposes an approach based on comparative domain corpora for feature-level SA. The proposed approach makes use of word associations for domain-specific feature extraction. First, we assign a similarity score for each candidate feature to denote its similarity extent to a domain. Then we identify domain features based on their similarity scores on different comparative domain corpora. After that, dependency grammar and a general sentiment lexicon are applied to extract and expand feature-oriented opinion words. Lastly, the semantic orientation of a domain-specific feature is determined based on the feature-oriented opinion lexicons. In evaluation, we compare the proposed method with several state-of-the-art methods (including unsupervised and semi-supervised) using a standard product review test collection. The experimental results demonstrate the effectiveness of using comparative domain corpora.

  14. Sentiment Prediction Based on Dempster-Shafer Theory of Evidence

    Directory of Open Access Journals (Sweden)

    Mohammad Ehsan Basiri

    2014-01-01

    Full Text Available Sentiment prediction techniques are often used to assign numerical scores to free-text format reviews written by people in online review websites. In order to exploit the fine-grained structural information of textual content, a review may be considered as a collection of sentences, each with its own sentiment orientation and score. In this manner, a score aggregation method is needed to combine sentence-level scores into an overall review rating. While recent work has concentrated on designing effective sentence-level prediction methods, there remains the problem of finding efficient algorithms for score aggregation. In this study, we investigate different aggregation methods, as well as the cases in which they perform poorly. According to the analysis of existing methods, we propose a new score aggregation method based on the Dempster-Shafer theory of evidence. In the proposed method, we first detect the polarity of reviews using a machine learning approach and then, consider sentence scores as evidence for the overall review rating. The results from two public social web datasets show the higher performance of our method in comparison with existing score aggregation methods and state-of-the-art machine learning approaches.

  15. Climate Change Sentiment on Twitter: An Unsolicited Public Opinion Poll.

    Directory of Open Access Journals (Sweden)

    Emily M Cody

    Full Text Available The consequences of anthropogenic climate change are extensively debated through scientific papers, newspaper articles, and blogs. Newspaper articles may lack accuracy, while the severity of findings in scientific papers may be too opaque for the public to understand. Social media, however, is a forum where individuals of diverse backgrounds can share their thoughts and opinions. As consumption shifts from old media to new, Twitter has become a valuable resource for analyzing current events and headline news. In this research, we analyze tweets containing the word "climate" collected between September 2008 and July 2014. Through use of a previously developed sentiment measurement tool called the Hedonometer, we determine how collective sentiment varies in response to climate change news, events, and natural disasters. We find that natural disasters, climate bills, and oil-drilling can contribute to a decrease in happiness while climate rallies, a book release, and a green ideas contest can contribute to an increase in happiness. Words uncovered by our analysis suggest that responses to climate change news are predominately from climate change activists rather than climate change deniers, indicating that Twitter is a valuable resource for the spread of climate change awareness.

  16. Climate Change Sentiment on Twitter: An Unsolicited Public Opinion Poll.

    Science.gov (United States)

    Cody, Emily M; Reagan, Andrew J; Mitchell, Lewis; Dodds, Peter Sheridan; Danforth, Christopher M

    2015-01-01

    The consequences of anthropogenic climate change are extensively debated through scientific papers, newspaper articles, and blogs. Newspaper articles may lack accuracy, while the severity of findings in scientific papers may be too opaque for the public to understand. Social media, however, is a forum where individuals of diverse backgrounds can share their thoughts and opinions. As consumption shifts from old media to new, Twitter has become a valuable resource for analyzing current events and headline news. In this research, we analyze tweets containing the word "climate" collected between September 2008 and July 2014. Through use of a previously developed sentiment measurement tool called the Hedonometer, we determine how collective sentiment varies in response to climate change news, events, and natural disasters. We find that natural disasters, climate bills, and oil-drilling can contribute to a decrease in happiness while climate rallies, a book release, and a green ideas contest can contribute to an increase in happiness. Words uncovered by our analysis suggest that responses to climate change news are predominately from climate change activists rather than climate change deniers, indicating that Twitter is a valuable resource for the spread of climate change awareness.

  17. 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

  18. 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

    2018-04-20

    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.

  19. 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

  20. 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

  1. 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.

  2. Sentiment Analysis of User-Generated Content on Drug Review Websites

    Directory of Open Access Journals (Sweden)

    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.

  3. 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

  4. 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)

  5. Discovering Fine-grained Sentiment in Suicide Notes.

    Science.gov (United States)

    Wang, Wenbo; Chen, Lu; Tan, Ming; Wang, Shaojun; Sheth, Amit P

    2012-01-01

    This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system gains a better trade-off between precision and recall, and yields the highest micro-averaged F-measure (0.5038), which is better than the mean (0.4875) and median (0.5027) micro-average F-measures among all participating teams.

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

    DEFF Research Database (Denmark)

    Piccolo, Sebastiano; Wilberg, Julian; Lindemann, Udo

    Changes are part of any project. Although previous research provides methods to deal with changes, understanding of changes in relation to sentiment is still unclear. This is important as people's mood can affect performance and decisions. We implement an approach to quantify "change language......" 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....

  7. 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

    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....

  8. Using Sentence-Level Classifiers for Cross-Domain Sentiment Analysis

    Science.gov (United States)

    2014-09-01

    sentiment have been developed. When applied to the never-ending stream of text data generated in social media , for example, we have a potentially rich...permettre aux utilisateurs d’examiner les opinions positives et négatives associées aux concepts. Les résultats n’ont pas été marquants. Plus précisément...pages 751–760, New York, NY, USA, 2010. ACM. [4] Bo Pang and Lillian Lee. A sentimental education : Sentiment analysis using subjectivity summarization

  9. 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)

  10. 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%.

  11. 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.

  12. 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.

  13. Dissemination Patterns and Associated Network Effects of Sentiments in Social Networks

    DEFF Research Database (Denmark)

    Hillmann, Robert; Trier, Matthias

    2012-01-01

    Communication in online social networks has been analyzed for some time regarding the expression of sentiments. So far, very little is known about the relationship between sentiments and network emergence, dissemination patterns and possible differences between positive and negative sentiments....... 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...

  14. Incorporating conditional random fields and active learning to improve sentiment identification.

    Science.gov (United States)

    Zhang, Kunpeng; Xie, Yusheng; Yang, Yi; Sun, Aaron; Liu, Hengchang; Choudhary, Alok

    2014-10-01

    Many machine learning, statistical, and computational linguistic methods have been developed to identify sentiment of sentences in documents, yielding promising results. However, most of state-of-the-art methods focus on individual sentences and ignore the impact of context on the meaning of a sentence. In this paper, we propose a method based on conditional random fields to incorporate sentence structure and context information in addition to syntactic information for improving sentiment identification. We also investigate how human interaction affects the accuracy of sentiment labeling using limited training data. We propose and evaluate two different active learning strategies for labeling sentiment data. Our experiments with the proposed approach demonstrate a 5%-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. 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...

  16. Does consumer sentiment predict consumer spending in Malaysia? an autoregressive distributed lag (ARDL) approach

    OpenAIRE

    Mohd Haniff, NorAzza; Masih, Mansur

    2016-01-01

    The purpose of this paper is to determine the nature of relationship between consumer sentiment and consumer spending in the Malaysian context. The autoregressive distributed lag (ARDL) methodology is employed to test this relationship, controlling for information in other financial and economic indicators. The stability of the functions is tested by CUSUM and CUSUMQ and no structural break was found. Overall, the results show that the Consumer Sentiment Index does not have any predictive val...

  17. Multi-class Sentiment Classification on Twitter using an Emoji Training Heuristic

    OpenAIRE

    Hallsmar, Fredrik; Palm, Jonas

    2016-01-01

    Sentiment analysis on social media is an important part of today's need for information gathering. Different machine learning techniques have been used in recent years, and usage of an emoticon heuristic to automatically annotate training sets has been a popular approach. As emojis are becoming more popular to use in text-based communication this thesis investigates the feasibility of an emoji training heuristic for multi-class sentiment analysis using a Multinomial Naive Bayes Classifier. Tr...

  18. Learning domain-specific sentiment lexicons with applications to recommender systems

    OpenAIRE

    Peleja, Filipa Alexandra de Madureira

    2015-01-01

    Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of...

  19. A System for Sentiment Analysis of Colloquial Arabic Using Human Computation

    Science.gov (United States)

    Al-Subaihin, Afnan S.; Al-Khalifa, Hend S.

    2014-01-01

    We present the implementation and evaluation of a sentiment analysis system that is conducted over Arabic text with evaluative content. Our system is broken into two different components. The first component is a game that enables users to annotate large corpuses of text in a fun manner. The game produces necessary linguistic resources that will be used by the second component which is the sentimental analyzer. Two different algorithms have been designed to employ these linguistic resources to analyze text and classify it according to its sentimental polarity. The first approach is using sentimental tag patterns, which reached a precision level of 56.14%. The second approach is the sentimental majority approach which relies on calculating the number of negative and positive phrases in the sentence and classifying the sentence according to the dominant polarity. The results after evaluating the system for the first sentimental majority approach yielded the highest accuracy level reached by our system which is 60.5% while the second variation scored an accuracy of 60.32%. PMID:24892064

  20. A System for Sentiment Analysis of Colloquial Arabic Using Human Computation

    Directory of Open Access Journals (Sweden)

    Afnan S. Al-Subaihin

    2014-01-01

    Full Text Available We present the implementation and evaluation of a sentiment analysis system that is conducted over Arabic text with evaluative content. Our system is broken into two different components. The first component is a game that enables users to annotate large corpuses of text in a fun manner. The game produces necessary linguistic resources that will be used by the second component which is the sentimental analyzer. Two different algorithms have been designed to employ these linguistic resources to analyze text and classify it according to its sentimental polarity. The first approach is using sentimental tag patterns, which reached a precision level of 56.14%. The second approach is the sentimental majority approach which relies on calculating the number of negative and positive phrases in the sentence and classifying the sentence according to the dominant polarity. The results after evaluating the system for the first sentimental majority approach yielded the highest accuracy level reached by our system which is 60.5% while the second variation scored an accuracy of 60.32%.

  1. Quantifying the effect of sentiment on information diffusion in social media

    Directory of Open Access Journals (Sweden)

    Emilio Ferrara

    2015-09-01

    Full Text Available Social media has become the main vehicle of information production and consumption online. Millions of users every day log on their Facebook or Twitter accounts to get updates and news, read about their topics of interest, and become exposed to new opportunities and interactions. Although recent studies suggest that the contents users produce will affect the emotions of their readers, we still lack a rigorous understanding of the role and effects of contents sentiment on the dynamics of information diffusion. This work aims at quantifying the effect of sentiment on information diffusion, to understand: (i whether positive conversations spread faster and/or broader than negative ones (or vice-versa; (ii what kind of emotions are more typical of popular conversations on social media; and, (iii what type of sentiment is expressed in conversations characterized by different temporal dynamics. Our findings show that, at the level of contents, negative messages spread faster than positive ones, but positive ones reach larger audiences, suggesting that people are more inclined to share and favorite positive contents, the so-called positive bias. As for the entire conversations, we highlight how different temporal dynamics exhibit different sentiment patterns: for example, positive sentiment builds up for highly-anticipated events, while unexpected events are mainly characterized by negative sentiment. Our contribution represents a step forward to understand how the emotions expressed in short texts correlate with their spreading in online social ecosystems, and may help to craft effective policies and strategies for content generation and diffusion.

  2. Nostalgia and Sentimentality Among Minority Elderly People (Bulgarian Roma People and Hungarians Living in Romania

    Directory of Open Access Journals (Sweden)

    Stanislava Stoyanova

    2015-04-01

    Full Text Available Nostalgia and sentimentality are very typical for the old age. There are some characteristics that are perceived as typical for the elderly people in the different cultures, such as being dependent, and needing long-term care. There are also some similarities between the population tendencies in Bulgaria and Romania. The simultaneously acceptance in European Union of both countries also suggests the existence of some similar attitudes towards the past among elderly minority people in both countries. The hypothesis of the study was that together with some similarities, the elderly people from both ethnic minorities in the two countries would differ cross-culturally in their sentimentality and nostalgia related to the past. Sentimentality and nostalgia in elderly minority people (26 Roma people in Bulgaria and 21 Hungarians in Romania were measured by means of a questionnaire created by Gergov & Stoyanova (2013. The results indicated that the Hungarian minority in Romania was more sentimental and nostalgic than the Roma minority in Bulgaria. More thoughts about the past reported the minority young elders than the minority oldest old. The females from the minority groups were more sentimental than the males from the minority groups. Higher sentimentality and nostalgia among elderly Hungarians could be explained by their higher conservatism and more satisfaction with the hystorical past than Roma people. Roma people living in institutions felt a sense of stability in their present and they shared some positive expectations for the future.

  3. 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

  4. THE SPANISH VERSION OF THE CRIMINAL SENTIMENT SCALE MODIFIED (CSS-M: FACTOR STRUCTURE, RELIABILITY, AND VALIDITY

    Directory of Open Access Journals (Sweden)

    Víctor Company Martínez

    2015-07-01

    Full Text Available The purpose of this study was to translate and validate the Criminal Sentiment Scale Modified (CSS-M, which measures the criminal attitudes into Spanish. Despite the large body of research proving their importance as one of the best predictors of criminal conduct, only a few measures have been psychometrically developed and validated, and none of them are available in the Spanish language. A sample of 153 male inmates from Penitentiary Brians I of the Catalan Prison Service (Spain participated voluntarily in the study (73.9% of Spanish nationality, mean age = 37.3 completed the final version of the Spanish adaptation. An exploratory factor analysis (EFA and a confirmatory factor analysis (CFA were conducted with all the scales simultaneously, showing that the underlying structure of the CSS-M was best explained by a two-factor solution: Sentiments toward the establishment and Criminality self-benefits. Moreover, a set of analyses of variance (ANOVA was also performed, validating the scale well. According to the results of the study, it was concluded that the Spanish version of the CSS-M has satisfactory psychometric properties, enabling its potential usefulness within the legal field of Spanish-speaking countries as a key element in crime prevention.

  5. ‘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.

  6. Sentiment Measured in Hospital Discharge Notes Is Associated with Readmission and Mortality Risk: An Electronic Health Record Study.

    Directory of Open Access Journals (Sweden)

    Thomas H McCoy

    Full Text Available Natural language processing tools allow the characterization of sentiment--that is, terms expressing positive and negative emotion--in text. Applying such tools to electronic health records may provide insight into meaningful patient or clinician features not captured in coded data alone. We performed sentiment analysis on 2,484 hospital discharge notes for 2,010 individuals from a psychiatric inpatient unit, as well as 20,859 hospital discharges for 15,011 individuals from general medical units, in a large New England health system between January 2011 and 2014. The primary measures of sentiment captured intensity of subjective positive or negative sentiment expressed in the discharge notes. Mean scores were contrasted between sociodemographic and clinical groups in mixed effects regression models. Discharge note sentiment was then examined for association with risk for readmission in Cox regression models. Discharge notes for individuals with greater medical comorbidity were modestly but significantly lower in positive sentiment among both psychiatric and general medical cohorts (p<0.001 in each. Greater positive sentiment at discharge was associated with significantly decreased risk of hospital readmission in each cohort (~12% decrease per standard deviation above the mean. Automated characterization of discharge notes in terms of sentiment identifies differences between sociodemographic groups, as well as in clinical outcomes, and is not explained by differences in diagnosis. Clinician sentiment merits investigation to understand why and how it reflects or impacts outcomes.

  7. 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...

  8. SentiHealth: creating health-related sentiment lexicon using hybrid approach.

    Science.gov (United States)

    Asghar, Muhammad Zubair; Ahmad, Shakeel; Qasim, Maria; Zahra, Syeda Rabail; Kundi, Fazal Masud

    2016-01-01

    The exponential increase in the health-related online reviews has played a pivotal role in the development of sentiment analysis systems for extracting and analyzing user-generated health reviews about a drug or medication. The existing general purpose opinion lexicons, such as SentiWordNet has a limited coverage of health-related terms, creating problems for the development of health-based sentiment analysis applications. In this work, we present a hybrid approach to create health-related domain specific lexicon for the efficient classification and scoring of health-related users' sentiments. The proposed approach is based on the bootstrapping modal, a dataset of health reviews, and corpus-based sentiment detection and scoring. In each of the iteration, vocabulary of the lexicon is updated automatically from an initial seed cache, irrelevant words are filtered, words are declared as medical or non-medical entries, and finally sentiment class and score is assigned to each of the word. The results obtained demonstrate the efficacy of the proposed technique.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Multilingual Connotation Frames: A Case Study on Social Media for Targeted Sentiment Analysis and Forecast

    Energy Technology Data Exchange (ETDEWEB)

    Rashkin, Hannah J.; Bell, Eric B.; Choi, Yejin; Volkova, Svitlana

    2017-07-30

    People around the globe respond to major real world events through social media. To study targeted public sentiments across many languages and geographic locations, we introduce multilingual connotation frames: an extension from English connotation frames of Rashkin et al. (2016) with 10 additional European languages, focusing on the implied sentiments among event participants engaged in a frame. As a case study, we present large scale analysis on targeted public sentiments using 1.2 million multilingual connotation frames extracted from Twitter. We rely on connotation frames to build models to forecast country-specific connotation dynamics – perspective change over time towards salient entities and events. Our results demonstrate that connotation dynamics can be accurately predicted up to half a week in advance.

  14. Lexicon-enhanced sentiment analysis framework using rule-based classification scheme.

    Science.gov (United States)

    Asghar, Muhammad Zubair; Khan, Aurangzeb; Ahmad, Shakeel; Qasim, Maria; Khan, Imran Ali

    2017-01-01

    With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analysis (SA) applications for decision making. In this work, we exploit the wealth of user reviews, available through the online forums, to analyze the semantic orientation of words by categorizing them into +ive and -ive classes to identify and classify emoticons, modifiers, general-purpose and domain-specific words expressed in the public's feedback about the products. However, the un-supervised learning approach employed in previous studies is becoming less efficient due to data sparseness, low accuracy due to non-consideration of emoticons, modifiers, and presence of domain specific words, as they may result in inaccurate classification of users' reviews. Lexicon-enhanced sentiment analysis based on Rule-based classification scheme is an alternative approach for improving sentiment classification of users' reviews in online communities. In addition to the sentiment terms used in general purpose sentiment analysis, we integrate emoticons, modifiers and domain specific terms to analyze the reviews posted in online communities. To test the effectiveness of the proposed method, we considered users reviews in three domains. The results obtained from different experiments demonstrate that the proposed method overcomes limitations of previous methods and the performance of the sentiment analysis is improved after considering emoticons, modifiers, negations, and domain specific terms when compared to baseline methods.

  15. 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.

  16. 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.

  17. Lexicon-enhanced sentiment analysis framework using rule-based classification scheme.

    Directory of Open Access Journals (Sweden)

    Muhammad Zubair Asghar

    Full Text Available With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analysis (SA applications for decision making. In this work, we exploit the wealth of user reviews, available through the online forums, to analyze the semantic orientation of words by categorizing them into +ive and -ive classes to identify and classify emoticons, modifiers, general-purpose and domain-specific words expressed in the public's feedback about the products. However, the un-supervised learning approach employed in previous studies is becoming less efficient due to data sparseness, low accuracy due to non-consideration of emoticons, modifiers, and presence of domain specific words, as they may result in inaccurate classification of users' reviews. Lexicon-enhanced sentiment analysis based on Rule-based classification scheme is an alternative approach for improving sentiment classification of users' reviews in online communities. In addition to the sentiment terms used in general purpose sentiment analysis, we integrate emoticons, modifiers and domain specific terms to analyze the reviews posted in online communities. To test the effectiveness of the proposed method, we considered users reviews in three domains. The results obtained from different experiments demonstrate that the proposed method overcomes limitations of previous methods and the performance of the sentiment analysis is improved after considering emoticons, modifiers, negations, and domain specific terms when compared to baseline methods.

  18. The perception of ethnic diversity and anti-immigrant sentiments: a multilevel analysis of local communities in Belgium

    NARCIS (Netherlands)

    Hooghe, Marc; de Vroome, Thomas

    2015-01-01

    Most of the literature suggests a positive relationship between immigrant concentration and anti-immigrant sentiments. The main goal of this study is to investigate the impact of both perceived and actual size of migrant populations on anti-immigrant sentiments. A representative survey of

  19. 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

  20. 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.

  1. Émeutes urbaines, sentiments d’injustice, mobilisations associatives

    Directory of Open Access Journals (Sweden)

    Éric Marlière

    2011-07-01

    Full Text Available Cet article a pour objectif l’appréhension des répertoires de mobilisations politiques des jeunes dits « des cités ». Pour cela, il faut nous intéresser aux modes de vie de ces jeunes structurés depuis plus de trente ans maintenant autour du chômage et de la précarité et des nouvelles formes de ségrégation. Cette situation engendre chez les jeunes une certaine frustration sociale se manifestant sous la forme d’un sentiment d’injustice plus ou moins diffus. Si les émeutes urbaines constituent le mode d’action le plus médiatique, un certain nombre de jeunes adultes originaires « des cités » réagissent à travers un ensemble d’initiatives associatives nationales et locales comme le montrent les dernières échéances électorales.Urban riots, feeling of injustice and associative mobilizationsThis article’s objective are the understanding of the directories of the political youth called “cities”. For this, we must concern ourselves with life’s styles of the young people structured over 30 years now about unemployment and job insecurity and new forms of segregation. This creates youth frustration manifested as a feeling of injustice more or less diffuse. If the urban riots of action in the most media, a number of young adults from the “cities” are responding through a number of national associations and local initiatives as evidenced by the recent elections.Revueltas urbanas, sentimientos de injusticia, formas asociativasEste artículo tiene como objetivo el aprehender las diferentes formas de las movilizaciones políticas de los jóvenes de los barrios desfavorecidos. Para cumplirlo es necesario que nos interesemos por las maneras de vivir de esos jóvenes cuyas vidas se desarrollan dentro del paro, la precariedad y nuevas formas de segregación. Esta situación engendra una gran frustración social con conciencia más o menos difusa de ser víctimas de injusticias. Si las revueltas urbanas constituyen la

  2. Information environment, market-wide sentiment and IPO initial returns: Evidence from analyst forecasts before listing

    Directory of Open Access Journals (Sweden)

    Hongjun Zhu

    2015-09-01

    Full Text Available Measuring the information environment of firms using analyst (price forecast bias and forecast dispersion before listing, we empirically examine the interactive influence of the information environment and market-wide sentiment on the initial returns of initial public offerings (IPOs. We find the smaller the analyst forecast bias/dispersion, the lower the effect market-wide sentiment has on IPO initial returns. This finding indicates that information asymmetry is a basic reason for noise trading occurs and demonstrates the positive effect of financial analysts during IPOs. In addition, the effect of analyst forecasts is more pronounced during periods of rising markets and when IPO prices are not regulated.

  3. FEASA: AN APPROACH TO RESOLVE SENTIMENT AND GENERATE FEATURE EXTRACTION MATRIX

    OpenAIRE

    AmeenaShad*, Manjunath H R

    2016-01-01

    Sentiment analysis is the study of classifying human’s sentiments, evaluations, attitudes, opinions about some topic, product, expressed in form of text or speech. As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. For a popular product, the number of reviews can be in hundreds or even thousands. This makes it difficult for a potential customer to read them to make an informed decision on whether to purchase the product. In o...

  4. Opinion Mining and Improvised Algorithm for Feature Reduction in Sentiment Analysis

    OpenAIRE

    Siddharth. J; Ashish .S; Shreyash.A; Rishi.A; Prashant.U

    2017-01-01

    Nowadays organisations use the power of the web to analyse the review of the product by customer. The organisation cannot trust star based reviews because it can be faked by robots. That is why textual review is preferable. Opinion mining is used to find the approximate sentiment of the review. Sentiment analysis is a part of opinion mining which helps an organisation to get valuable feedback of the product by extracting the polarity of reviews. The review of a product may be used to improve ...

  5. Crowdsourced real-world sensing: sentiment analysis and the real-time web

    OpenAIRE

    Bermingham, Adam; Smeaton, Alan F.

    2010-01-01

    The advent of the real-time web is proving both challeng- ing and at the same time disruptive for a number of areas of research, notably information retrieval and web data mining. As an area of research reaching maturity, sentiment analysis oers a promising direction for modelling the text content available in real-time streams. This paper reviews the real-time web as a new area of focus for sentiment analysis and discusses the motivations and challenges behind such a direction.

  6. 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

  7. Popular and Classical Female Singers: Acoustic Comparison of Voice Use in the Song Melodia Sentimental (Sentimental Melody) by Heitor Villa-Lobos.

    Science.gov (United States)

    Sanchez Escamez, Natalia Eugenia; Guimarães Silva, Ana Paula; Assumpção de Andrada E Silva, Marta

    2017-12-29

    This study aims to compare acoustic characteristics of classical and popular female singers' vocal performances in Heitor Villa-Lobos' Melodia Sentimental (Sentimental Melody). Long-term average spectrum acoustic analysis and long-term voice onset time (VOT) were performed for two consonants /d/ in the first six verses of Melodia Sentimental sang by 10 professional singers: five classical (GC) and five popular (GP). Classical singers presented prominence in the region of the frequencies between 2.5 and 3.5 kHz, not observed in the majority of the popular singers' group. The GC group showed lighter spectral decline curves and the numerical value of decline was also lower. Classical singers presented lower long-term voice onset time values, which indicates a longer period of glottic closure. Acoustic analysis revealed that classical singers have more energy in glottic closure associated with a shorter duration of glottic coaptation. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  8. Smoking among construction workers: the nonlinear influence of the economy, cigarette prices, and antismoking sentiment.

    Science.gov (United States)

    Okechukwu, Cassandra; Bacic, Janine; Cheng, Kai-Wen; Catalano, Ralph

    2012-10-01

    Little research has been conducted on the influence of macroeconomic environments on smoking among blue-collar workers, a group with high smoking prevalence and that is especially vulnerable to the effects of changing economic circumstances. Using data from 52,418 construction workers in the Tobacco Use Supplement to the United States Current Population Survey, we examined the association of labor market shock, cigarette prices, and state antismoking sentiments with smoking status and average number of cigarettes smoked daily. Data analysis included the use of multiple linear and logistic regressions, which employed the sampling and replicate weights to account for sampling design. Unemployed, American-Indian, lower-educated and lower-income workers had higher smoking rates. Labor market shock had a quadratic association, which was non-significant for smoking status and significant for number of cigarettes. The association of cigarette prices with smoking status became non-significant after adjusting for state-level antismoking sentiment. State-level antismoking sentiment had significant quadratic association with smoking status among employed workers and significant quadratic association with number of cigarettes for all smokers. The study highlights how both workplace-based smoking cessation interventions and antismoking sentiments could further contribute to disparities in smoking by employment status. Copyright © 2012 Elsevier Ltd. All rights reserved.

  9. Prediction of advertisement preference by fusing EEG response and sentiment analysis.

    Science.gov (United States)

    Gauba, Himaanshu; Kumar, Pradeep; Roy, Partha Pratim; Singh, Priyanka; Dogra, Debi Prosad; Raman, Balasubramanian

    2017-08-01

    This paper presents a novel approach to predict rating of video-advertisements based on a multimodal framework combining physiological analysis of the user and global sentiment-rating available on the internet. We have fused Electroencephalogram (EEG) waves of user and corresponding global textual comments of the video to understand the user's preference more precisely. In our framework, the users were asked to watch the video-advertisement and simultaneously EEG signals were recorded. Valence scores were obtained using self-report for each video. A higher valence corresponds to intrinsic attractiveness of the user. Furthermore, the multimedia data that comprised of the comments posted by global viewers, were retrieved and processed using Natural Language Processing (NLP) technique for sentiment analysis. Textual contents from review comments were analyzed to obtain a score to understand sentiment nature of the video. A regression technique based on Random forest was used to predict the rating of an advertisement using EEG data. Finally, EEG based rating is combined with NLP-based sentiment score to improve the overall prediction. The study was carried out using 15 video clips of advertisements available online. Twenty five participants were involved in our study to analyze our proposed system. The results are encouraging and these suggest that the proposed multimodal approach can achieve lower RMSE in rating prediction as compared to the prediction using only EEG data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Discovering public sentiment in social media for predicting stock movement of publicly listed companies

    NARCIS (Netherlands)

    Li, Bing; Chan, Keith; Ou, Carol; Sun, Ruifeng

    The popularity of many social media sites has prompted both academic and practical research on the possibility of mining social media data for the analysis of public sentiment. Studies have suggested that public emotions shown through Twitter could be well correlated with the Dow Jones Industrial

  11. 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.

  12. 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%.

  13. 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

  14. 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.

  15. Care more about customers: unsupervised domain-independent aspect detection for sentiment analysis of customer reviews

    NARCIS (Netherlands)

    Bagheri, Ayoub; Saraee, Mohamad; de Jong, Franciska M.G.

    2013-01-01

    With the rapid growth of user-generated content on the internet, automatic sentiment analysis of online customer reviews has become a hot research topic recently, but due to variety and wide range of products and services being reviewed on the internet, the supervised and domain-specific models are

  16. 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.

  17. 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.

  18. 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.

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

    Science.gov (United States)

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

    2018-01-01

    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. PMID:29393869

  20. Feasibility of real-time satisfaction surveys through automated analysis of patients' unstructured comments and sentiments.

    Science.gov (United States)

    Alemi, Farrokh; Torii, Manabu; Clementz, Laura; Aron, David C

    2012-01-01

    This article shows how sentiment analysis (an artificial intelligence procedure that classifies opinions expressed within the text) can be used to design real-time satisfaction surveys. To improve participation, real-time surveys must be radically short. The shortest possible survey is a comment card. Patients' comments can be found online at sites organized for rating clinical care, within e-mails, in hospital complaint registries, or through simplified satisfaction surveys such as "Minute Survey." Sentiment analysis uses patterns among words to classify a comment into a complaint, or praise. It further classifies complaints into specific reasons for dissatisfaction, similar to broad categories found in longer surveys such as Consumer Assessment of Healthcare Providers and Systems. In this manner, sentiment analysis allows one to re-create responses to longer satisfaction surveys from a list of comments. To demonstrate, this article provides an analysis of sentiments expressed in 995 online comments made at the RateMDs.com Web site. We focused on pediatrician and obstetrician/gynecologist physicians in District of Columbia, Maryland, and Virginia. We were able to classify patients' reasons for dissatisfaction and the analysis provided information on how practices can improve their care. This article reports the accuracy of classifications of comments. Accuracy will improve as the number of comments received increases. In addition, we ranked physicians using the concept of time-to-next complaint. A time-between control chart was used to assess whether time-to-next complaint exceeded historical patterns and therefore suggested a departure from norms. These findings suggest that (1) patients' comments are easily available, (2) sentiment analysis can classify these comments into complaints/praise, and (3) time-to-next complaint can turn these classifications into numerical benchmarks that can trace impact of improvements over time. The procedures described in the

  1. Leveraging machine learning-based approaches to assess human papillomavirus vaccination sentiment trends with Twitter data.

    Science.gov (United States)

    Du, Jingcheng; Xu, Jun; Song, Hsing-Yi; Tao, Cui

    2017-07-05

    As one of the serious public health issues, vaccination refusal has been attracting more and more attention, especially for newly approved human papillomavirus (HPV) vaccines. Understanding public opinion towards HPV vaccines, especially concerns on social media, is of significant importance for HPV vaccination promotion. In this study, we leveraged a hierarchical machine learning based sentiment analysis system to extract public opinions towards HPV vaccines from Twitter. English tweets containing HPV vaccines-related keywords were collected from November 2, 2015 to March 28, 2016. Manual annotation was done to evaluate the performance of the system on the unannotated tweets corpus. Followed time series analysis was applied to this corpus to track the trends of machine-deduced sentiments and their associations with different days of the week. The evaluation of the unannotated tweets corpus showed that the micro-averaging F scores have reached 0.786. The learning system deduced the sentiment labels for 184,214 tweets in the collected unannotated tweets corpus. Time series analysis identified a coincidence between mainstream outcome and Twitter contents. A weak trend was found for "Negative" tweets that decreased firstly and began to increase later; an opposite trend was identified for "Positive" tweets. Tweets that contain the worries on efficacy for HPV vaccines showed a relative significant decreasing trend. Strong associations were found between some sentiments ("Positive", "Negative", "Negative-Safety" and "Negative-Others") with different days of the week. Our efforts on sentiment analysis for newly approved HPV vaccines provide us an automatic and instant way to extract public opinion and understand the concerns on Twitter. Our approaches can provide a feedback to public health professionals to monitor online public response, examine the effectiveness of their HPV vaccination promotion strategies and adjust their promotion plans.

  2. "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

  3. 'She Fell Senseless on His Corpse': The Woman of Feeling and the Sentimental Swoon in Eighteenth-Century Fiction

    OpenAIRE

    Csengei, Ildiko

    2008-01-01

    This essay deals with typical signs of female sentimental emotional response in eighteenth-century novels, including Sarah Fieldings The History of Ophelia (1760), Jean-Jacques Rousseau's Julie, or the New Heloise (1761), and Elizabeth Inchbald's A Simple Story (1791). The female sentimental repertoire of psychosomatic fainting, silences, sighs, palpitations and states of mental distraction is frequently taken for granted, but rarely thoroughly explored by scholarship dealing with the culture...

  4. Role of propagation thresholds in sentiment-based model of opinion evolution with information diffusion

    Science.gov (United States)

    Si, Xia-Meng; Wang, Wen-Dong; Ma, Yan

    2016-06-01

    The degree of sentiment is the key factor for internet users in determining their propagating behaviors, i.e. whether participating in a discussion and whether withdrawing from a discussion. For this end, we introduce two sentiment-based propagation thresholds (i.e. infected threshold and refractory threshold) and propose an interacting model based on the Bayesian updating rules. Our model describe the phenomena that few internet users change their decisions and that someone has drop out of discussion about the topic when some others are just aware of it. Numerical simulations show that, large infected threshold restrains information diffusion but favors the lessening of extremism, while large refractory threshold facilitates decision interaction but promotes the extremism. Making netizens calm down and propagate information sanely can restrain the prevailing of extremism about rumors.

  5. Sentiment Analysis in Spanish for Improvement of Products and Services: A Deep Learning Approach

    Directory of Open Access Journals (Sweden)

    Mario Andrés Paredes-Valverde

    2017-01-01

    Full Text Available Sentiment analysis is an important area that allows knowing public opinion of the users about several aspects. This information helps organizations to know customer satisfaction. Social networks such as Twitter are important information channels because information in real time can be obtained and processed from them. In this sense, we propose a deep-learning-based approach that allows companies and organizations to detect opportunities for improving the quality of their products or services through sentiment analysis. This approach is based on convolutional neural network (CNN and word2vec. To determine the effectiveness of this approach for classifying tweets, we conducted experiments with different sizes of a Twitter corpus composed of 100000 tweets. We obtained encouraging results with a precision of 88.7%, a recall of 88.7%, and an F-measure of 88.7% considering the complete dataset.

  6. 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.

  7. Economic Crisis and Anti-Immigrant Sentiment: The Case of Andalusia

    Directory of Open Access Journals (Sweden)

    Sebastian Rinken

    2016-01-01

    Full Text Available This paper provides three interrelated reasons not to confound perceptions of economic group-threat with hostility toward people of foreign origin. Firstly, I argue that expansive notions of prejudice impede analyzing attitudes toward immigration and immigrants with sufficient precision. Secondly, the recent evolution in the Southern Spanish region of Andalusia illustrates divergent trajectories: anti-immigrant sentiment remained subdued despite surging unemployment and perceived conflict-of-interest. Thirdly, various factors are found to contain antiimmigrant sentiment amidst inauspicious economic circumstances and regardless of perceived group-competition. The study shows that attitudes towards immigrants hinge on a complex array of predispositions and perceptions, rather than economic facts and interests per se.

  8. 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.

  9. 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.

  10. Smoking among construction workers: The nonlinear influence of the economy, cigarette prices, and antismoking sentiment

    OpenAIRE

    Okechukwu, Cassandra; Bacic, Janine; Cheng, Kai-Wen; Catalano, Ralph

    2012-01-01

    Little research has been conducted on the influence of macroeconomic environments on smoking among blue-collar workers, a group with high smoking prevalence and that is especially vulnerable to the effects of changing economic circumstances. Using data from 52,418 construction workers in the Tobacco Use Supplement to the United States Current Population Survey, we examined the association of labor market shock, cigarette prices, and state antismoking sentiments with smoking status and average...

  11. 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

  12. White sympathy: race and moral sentiments from the man of feeling to the new woman

    OpenAIRE

    Sorensen, Lise Moller

    2010-01-01

    This PhD thesis explores the role of sympathy in the discursive formation of race in Scottish and American eighteenth- and nineteenth-century literature. Offering insight into Adam Smith’s Theory of Moral Sentiments as one paradigm that underpins the philosophical terms of sympathy in the Atlantic world, I argue that sympathy as a mode of control and a mechanism of normalisation played a formative role in the transatlantic history of the literary construction of whiteness. M...

  13. Use of sentiment analysis for capturing patient experience from free-text comments posted online.

    Science.gov (United States)

    Greaves, Felix; Ramirez-Cano, Daniel; Millett, Christopher; Darzi, Ara; Donaldson, Liam

    2013-11-01

    There are large amounts of unstructured, free-text information about quality of health care available on the Internet in blogs, social networks, and on physician rating websites that are not captured in a systematic way. New analytical techniques, such as sentiment analysis, may allow us to understand and use this information more effectively to improve the quality of health care. We attempted to use machine learning to understand patients' unstructured comments about their care. We used sentiment analysis techniques to categorize online free-text comments by patients as either positive or negative descriptions of their health care. We tried to automatically predict whether a patient would recommend a hospital, whether the hospital was clean, and whether they were treated with dignity from their free-text description, compared to the patient's own quantitative rating of their care. We applied machine learning techniques to all 6412 online comments about hospitals on the English National Health Service website in 2010 using Weka data-mining software. We also compared the results obtained from sentiment analysis with the paper-based national inpatient survey results at the hospital level using Spearman rank correlation for all 161 acute adult hospital trusts in England. There was 81%, 84%, and 89% agreement between quantitative ratings of care and those derived from free-text comments using sentiment analysis for cleanliness, being treated with dignity, and overall recommendation of hospital respectively (kappa scores: .40-.74, P<.001 for all). We observed mild to moderate associations between our machine learning predictions and responses to the large patient survey for the three categories examined (Spearman rho 0.37-0.51, P<.001 for all). The prediction accuracy that we have achieved using this machine learning process suggests that we are able to predict, from free-text, a reasonably accurate assessment of patients' opinion about different performance aspects of

  14. Lexicon-enhanced sentiment analysis framework using rule-based classification scheme

    OpenAIRE

    Asghar, Muhammad Zubair; Khan, Aurangzeb; Ahmad, Shakeel; Qasim, Maria; Khan, Imran Ali

    2017-01-01

    With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analy...

  15. 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.

  16. 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%.

  17. Assessing and responding in real time to online anti-vaccine sentiment during a flu pandemic.

    Science.gov (United States)

    Seeman, Neil; Ing, Alton; Rizo, Carlos

    2010-01-01

    The perceived safety of vaccination is an important explanatory factor for vaccine uptake and, consequently, for rates of illness and death. The objectives of this study were (1) to evaluate Canadian attitudes around the safety of the H1N1 vaccine during the fall 2009 influenza pandemic and (2) to consider how public health communications can leverage the Internet to counteract, in real time, anti-vaccine sentiment. We surveyed a random sample of 175,257 Canadian web users from October 27 to November 19, 2009, about their perceptions of the safety of the HINI vaccine. In an independent analysis, we also assessed the popularity of online flu vaccine-related information using a tool developed for this purpose. A total of 27,382 unique online participants answered the survey (15.6% response rate). Of the respondents, 23.4% considered the vaccine safe, 41.4% thought it was unsafe and 35.2% reported ambivalence over its safety. Websites and blog posts with anti-vaccine sentiment remained popular during the course of the pandemic. Current public health communication and education strategies about the flu vaccine can be complemented by web analytics that identify, track and neutralize anti-vaccine sentiment on the Internet, thus increasing perceived vaccine safety. Counter-marketing strategies can be transparent and collaborative, engaging online "influencers" who spread misinformation.

  18. 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).

  19. 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%.

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

    OpenAIRE

    Stanislava Yordanova Stoyanova; Vaitsa Giannouli; Teodor Krasimirov Gergov

    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 Bulg...

  1. 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.

  2. 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

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

    Directory of Open Access Journals (Sweden)

    Stanislava Yordanova Stoyanova

    2017-03-01

    Full Text Available 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.

  4. Economic Forces, Sentiment and Emerging Eastern European Stock Markets

    OpenAIRE

    Dmitrij Celov; Žana Grigaliuniene

    2010-01-01

    The aim of the current study is to explore the effect of macroeconomic news on stock returns in Eastern European countries, combining market and macroeconomic data over the period of 2000-2009, during which the markets experienced excessive optimistic and pessimistic episodes. Hypothesising the asymmetry in stock price responses to good and bad news, we seek to test its degree under the specific market conditions. The error correction models for each country are extended with fixed effects pa...

  5. 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.

  6. Prediction of venous thromboembolism using semantic and sentiment analyses of clinical narratives.

    Science.gov (United States)

    Sabra, Susan; Mahmood Malik, Khalid; Alobaidi, Mazen

    2018-03-01

    Venous thromboembolism (VTE) is the third most common cardiovascular disorder. It affects people of both genders at ages as young as 20 years. The increased number of VTE cases with a high fatality rate of 25% at first occurrence makes preventive measures essential. Clinical narratives are a rich source of knowledge and should be included in the diagnosis and treatment processes, as they may contain critical information on risk factors. It is very important to make such narrative blocks of information usable for searching, health analytics, and decision-making. This paper proposes a Semantic Extraction and Sentiment Assessment of Risk Factors (SESARF) framework. Unlike traditional machine-learning approaches, SESARF, which consists of two main algorithms, namely, ExtractRiskFactor and FindSeverity, prepares a feature vector as the input to a support vector machine (SVM) classifier to make a diagnosis. SESARF matches and maps the concepts of VTE risk factors and finds adjectives and adverbs that reflect their levels of severity. SESARF uses a semantic- and sentiment-based approach to analyze clinical narratives of electronic health records (EHR) and then predict a diagnosis of VTE. We use a dataset of 150 clinical narratives, 80% of which are used to train our prediction classifier support vector machine, with the remaining 20% used for testing. Semantic extraction and sentiment analysis results yielded precisions of 81% and 70%, respectively. Using a support vector machine, prediction of patients with VTE yielded precision and recall values of 54.5% and 85.7%, respectively. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  7. JU_KS@SAIL_CodeMixed-2017: Sentiment Analysis for Indian Code Mixed Social Media Texts

    OpenAIRE

    Sarkar, Kamal

    2018-01-01

    This paper reports about our work in the NLP Tool Contest @ICON-2017, shared task on Sentiment Analysis for Indian Languages (SAIL) (code mixed). To implement our system, we have used a machine learning algo-rithm called Multinomial Na\\"ive Bayes trained using n-gram and SentiWordnet features. We have also used a small SentiWordnet for English and a small SentiWordnet for Bengali. But we have not used any SentiWordnet for Hindi language. We have tested our system on Hindi-English and Bengali-...

  8. Sentiment Analysis: How to Derive Prior Polarities from SentiWordNet

    OpenAIRE

    Guerini, Marco; Gatti, Lorenzo; Turchi, Marco

    2013-01-01

    Assigning a positive or negative score to a word out of context (i.e. a word's prior polarity) is a challenging task for sentiment analysis. In the literature, various approaches based on SentiWordNet have been proposed. In this paper, we compare the most often used techniques together with newly proposed ones and incorporate all of them in a learning framework to see whether blending them can further improve the estimation of prior polarity scores. Using two different versions of SentiWordNe...

  9. 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.

  10. 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...

  11. Adding a Capability to Extract Sentiment from Text Using HanDles

    Science.gov (United States)

    2012-05-01

    to those issues, or how that author feels about them. The area of automated opinion mining and sentiment analysis (OMSA) uses natural language ...I’m not going to give the plot away, but if you like your Clint Eastwood as a hard-nosed tough guy with foul language alla Dirty Harry or Heartbreak...such a disaster. Especially given Swardson’s stellar performance in Just Go With It. This movie is not a flop, its not an " oops ", its not a mistake

  12. 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.

  13. Sentimental tourism as one of the newest ways of enhancement and development of Ukrainian-Polish relations

    Directory of Open Access Journals (Sweden)

    Kopachynska Galina Vasylivna

    2017-07-01

    Full Text Available The article deals with different theoretical approaches to the categorization of the «sentimental tourism». It characterizes the main features of the sentimental tourism organization in the Volyn region as well as its influence on the enhancement of foreign relations between Ukraine and the Republic of Poland. The paper defines the historical places of polish nationality representatives settled in Volyn before the resettlement period after WWII along territory of modern Poland and the burial places of foreign citizens in the area. These places are identified as basic resources for the development of sentimental tourism in the region and as promising areas for investment and international cooperation of both countries. The authors describe the current legal framework of cooperation between Ukraine and Poland on this issue.

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

    Directory of Open Access Journals (Sweden)

    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

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  17. Intelligent Topical Sentiment Analysis for the Classification of E-Learners and Their Topics of Interest

    Directory of Open Access Journals (Sweden)

    M. Ravichandran

    2015-01-01

    Full Text Available Every day, huge numbers of instant tweets (messages are published on Twitter as it is one of the massive social media for e-learners interactions. The options regarding various interesting topics to be studied are discussed among the learners and teachers through the capture of ideal sources in Twitter. The common sentiment behavior towards these topics is received through the massive number of instant messages about them. In this paper, rather than using the opinion polarity of each message relevant to the topic, authors focus on sentence level opinion classification upon using the unsupervised algorithm named bigram item response theory (BIRT. It differs from the traditional classification and document level classification algorithm. The investigation illustrated in this paper is of threefold which are listed as follows: (1 lexicon based sentiment polarity of tweet messages; (2 the bigram cooccurrence relationship using naïve Bayesian; (3 the bigram item response theory (BIRT on various topics. It has been proposed that a model using item response theory is constructed for topical classification inference. The performance has been improved remarkably using this bigram item response theory when compared with other supervised algorithms. The experiment has been conducted on a real life dataset containing different set of tweets and topics.

  18. Preparation of Improved Turkish DataSet for Sentiment Analysis in Social Media

    Directory of Open Access Journals (Sweden)

    Makinist Semiha

    2017-01-01

    Full Text Available A public dataset, with a variety of properties suitable for sentiment analysis [1], event prediction, trend detection and other text mining applications, is needed in order to be able to successfully perform analysis studies. The vast majority of data on social media is text-based and it is not possible to directly apply machine learning processes into these raw data, since several different processes are required to prepare the data before the implementation of the algorithms. For example, different misspellings of same word enlarge the word vector space unnecessarily, thereby it leads to reduce the success of the algorithm and increase the computational power requirement. This paper presents an improved Turkish dataset with an effective spelling correction algorithm based on Hadoop [2]. The collected data is recorded on the Hadoop Distributed File System and the text based data is processed by MapReduce programming model. This method is suitable for the storage and processing of large sized text based social media data. In this study, movie reviews have been automatically recorded with Apache ManifoldCF (MCF [3] and data clusters have been created. Various methods compared such as Levenshtein and Fuzzy String Matching have been proposed to create a public dataset from collected data. Experimental results show that the proposed algorithm, which can be used as an open source dataset in sentiment analysis studies, have been performed successfully to the detection and correction of spelling errors.

  19. 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.

  20. 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.

  1. 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

  2. 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…

  3. "My Invisalign experience" : Content, metrics and comment sentiment analysis of the most popular patient testimonials on YouTube

    NARCIS (Netherlands)

    Livas, Christos; Delli, Konstantina; Pandis, Nikolaos

    2018-01-01

    BACKGROUND: The aim of the study was to investigate the popularity, content of Invisalign patient testimonials on YouTube, as well as the sentiment of the related comments. METHODS: Using the term "Invisalign experience," the top 100 results on YouTube by view count were screened for English spoken

  4. 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).

  5. 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

  6. 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%

  7. 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.

  8. Cosmopolitan Sentiments After 9-11: Trauma and the Politics of Vulnerability

    Directory of Open Access Journals (Sweden)

    James Brassett

    2010-01-01

    Full Text Available The paper provides a critical analysis of the possibility of a cosmopolitan response to traumatic events like 9-11. While cosmopolitan sentiments are celebrated for highlighting the question of vulnerability, it is argued that such questions are always-already rendered according to practices of governance that are ethically and politically problematic. In this sense, the paper explores what it calls the ‘politics of vulnerability’ via a critical engagement with David Held’s version of cosmopolitan democracy, followed by a problematisation of psychological structures of knowledge about trauma. Beyond the tranquilising effects of universal norms and/or the scientific certainty of trauma counselling, the paper makes the case for developing an acute empirical politics of the subjects of trauma. Ultimately, this argument does not then turn into a rejection ofcosmopolitan democracy, so much as a call for its further politicisation and continuous engagement.

  9. Using ensemble models to classify the sentiment expressed in suicide notes.

    Science.gov (United States)

    McCart, James A; Finch, Dezon K; Jarman, Jay; Hickling, Edward; Lind, Jason D; Richardson, Matthew R; Berndt, Donald J; Luther, Stephen L

    2012-01-01

    In 2007, suicide was the tenth leading cause of death in the U.S. Given the significance of this problem, suicide was the focus of the 2011 Informatics for Integrating Biology and the Bedside (i2b2) Natural Language Processing (NLP) shared task competition (track two). Specifically, the challenge concentrated on sentiment analysis, predicting the presence or absence of 15 emotions (labels) simultaneously in a collection of suicide notes spanning over 70 years. Our team explored multiple approaches combining regular expression-based rules, statistical text mining (STM), and an approach that applies weights to text while accounting for multiple labels. Our best submission used an ensemble of both rules and STM models to achieve a micro-averaged F(1) score of 0.5023, slightly above the mean from the 26 teams that competed (0.4875).

  10. 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.

  11. Suicide note sentiment classification: a supervised approach augmented by web data.

    Science.gov (United States)

    Xu, Yan; Wang, Yue; Liu, Jiahua; Tu, Zhuowen; Sun, Jian-Tao; Tsujii, Junichi; Chang, Eric

    2012-01-01

    To create a sentiment classification system for the Fifth i2b2/VA Challenge Track 2, which can identify thirteen subjective categories and two objective categories. We developed a hybrid system using Support Vector Machine (SVM) classifiers with augmented training data from the Internet. Our system consists of three types of classification-based systems: the first system uses spanning n-gram features for subjective categories, the second one uses bag-of-n-gram features for objective categories, and the third one uses pattern matching for infrequent or subtle emotion categories. The spanning n-gram features are selected by a feature selection algorithm that leverages emotional corpus from weblogs. Special normalization of objective sentences is generalized with shallow parsing and external web knowledge. We utilize three sources of web data: the weblog of LiveJournal which helps to improve the feature selection, the eBay List which assists in special normalization of information and instructions categories, and the suicide project web which provides unlabeled data with similar properties as suicide notes. The performance is evaluated by the overall micro-averaged precision, recall and F-measure. Our system achieved an overall micro-averaged F-measure of 0.59. Happiness_peacefulness had the highest F-measure of 0.81. We were ranked as the second best out of 26 competing teams. Our results indicated that classifying fine-grained sentiments at sentence level is a non-trivial task. It is effective to divide categories into different groups according to their semantic properties. In addition, our system performance benefits from external knowledge extracted from publically available web data of other purposes; performance can be further enhanced when more training data is available.

  12. Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses.

    Science.gov (United States)

    Oksanen, Atte; Garcia, David; Sirola, Anu; Näsi, Matti; Kaakinen, Markus; Keipi, Teo; Räsänen, Pekka

    2015-11-12

    Pro-anorexia communities exist online and encourage harmful weight loss and weight control practices, often through emotional content that enforces social ties within these communities. User-generated responses to videos that directly oppose pro-anorexia communities have not yet been researched in depth. The aim was to study emotional reactions to pro-anorexia and anti-pro-anorexia online content on YouTube using sentiment analysis. Using the 50 most popular YouTube pro-anorexia and anti-pro-anorexia user channels as a starting point, we gathered data on users, their videos, and their commentators. A total of 395 anorexia videos and 12,161 comments were analyzed using positive and negative sentiments and ratings submitted by the viewers of the videos. The emotional information was automatically extracted with an automatic sentiment detection tool whose reliability was tested with human coders. Ordinary least squares regression models were used to estimate the strength of sentiments. The models controlled for the number of video views and comments, number of months the video had been on YouTube, duration of the video, uploader's activity as a video commentator, and uploader's physical location by country. The 395 videos had more than 6 million views and comments by almost 8000 users. Anti-pro-anorexia video comments expressed more positive sentiments on a scale of 1 to 5 (adjusted prediction [AP] 2.15, 95% CI 2.11-2.19) than did those of pro-anorexia videos (AP 2.02, 95% CI 1.98-2.06). Anti-pro-anorexia videos also received more likes (AP 181.02, 95% CI 155.19-206.85) than pro-anorexia videos (AP 31.22, 95% CI 31.22-37.81). Negative sentiments and video dislikes were equally distributed in responses to both pro-anorexia and anti-pro-anorexia videos. Despite pro-anorexia content being widespread on YouTube, videos promoting help for anorexia and opposing the pro-anorexia community were more popular, gaining more positive feedback and comments than pro-anorexia videos

  13. 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

  14. 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

  15. La publicidad de lo íntimo. El Epistolario Sentimental de la revista Para Ti [1924-1933

    Directory of Open Access Journals (Sweden)

    Paula Bontempo

    2011-04-01

    Full Text Available Para Ti, el semanario femenino de Editorial Atlántida apareció en el mercado en 1922 como una revista de servicios multipropósitos. El presente artículo se propone estudiar el Epistolario Sentimental, columna que intentaba dar respuesta a los conflictos del corazón. Esta sección constituyó un lugar para hablar de temas que en el resto de la revista no se trataban. Así, la sexualidad, la sensualidad, los deseos y los conflictos familiares ingresaron en el mundo de Para Ti y de su público a través de un canal marginal. En este sentido, el Epistolario Sentimental constituye un espacio privilegiado para analizar tensiones y cambios en las costumbres y la moral

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. The Practice of Sustainable Facilities Management: Design Sentiments and the Knowledge Chasm

    Directory of Open Access Journals (Sweden)

    Abbas Elmualim

    2009-12-01

    Full Text Available The construction industry with its nature of project delivery is very fragmented in terms of the various processes that encompass design, construction, facilities and assets management. Facilities managers are in the forefront of delivering sustainable assets management and hence further the venture for mitigation and adaptation to climate change. A questionnaire survey was conducted to establish perceptions, level of commitment and knowledge chasm in practising sustainable facilities management (FM. This has significant implications for sustainable design management, especially in a fragmented industry. The majority of questionnaire respondents indicated the importance of sustainability for their organization. Many of them stated that they reported on sustainability as part of their organization annual reporting with energy efficiency, recycling and waste reduction as the main concern for them. The overwhelming barrier for implementing sound, sustainable FM is the lack of consensual understanding and focus of individuals and organizations about sustainability. There is a knowledge chasm regarding practical information on delivering sustainable FM. Sustainability information asymmetry in design, construction and FM processes render any sustainable design as a sentiment and mere design aspiration. Skills and training provision, traditionally offered separately to designers and facilities managers, needs to be re-evaluated. Sustainability education and training should be developed to provide effective structures and processes to apply sustainability throughout the construction and FM industries coherently and as common practice. Published in the Journal AEDM - Volume 5, Numbers 1-2, 2009 , pp. 91-102(12

  1. 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.

  2. Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

    Science.gov (United States)

    Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

    2017-10-01

    This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

  3. Optimization on machine learning based approaches for sentiment analysis on HPV vaccines related tweets.

    Science.gov (United States)

    Du, Jingcheng; Xu, Jun; Song, Hsingyi; Liu, Xiangyu; Tao, Cui

    2017-03-03

    Analysing public opinions on HPV vaccines on social media using machine learning based approaches will help us understand the reasons behind the low vaccine coverage and come up with corresponding strategies to improve vaccine uptake. To propose a machine learning system that is able to extract comprehensive public sentiment on HPV vaccines on Twitter with satisfying performance. We collected and manually annotated 6,000 HPV vaccines related tweets as a gold standard. SVM model was chosen and a hierarchical classification method was proposed and evaluated. Additional feature sets evaluation and model parameters optimization was done to maximize the machine learning model performance. A hierarchical classification scheme that contains 10 categories was built to access public opinions toward HPV vaccines comprehensively. A 6,000 annotated tweets gold corpus with Kappa annotation agreement at 0.851 was created and made public available. The hierarchical classification model with optimized feature sets and model parameters has increased the micro-averaging and macro-averaging F score from 0.6732 and 0.3967 to 0.7442 and 0.5883 respectively, compared with baseline model. Our work provides a systematical way to improve the machine learning model performance on the highly unbalanced HPV vaccines related tweets corpus. Our system can be further applied on a large tweets corpus to extract large-scale public opinion towards HPV vaccines.

  4. Predicting HCAHPS scores from hospitals' social media pages: A sentiment analysis.

    Science.gov (United States)

    Huppertz, John W; Otto, Peter

    2017-02-22

    Social media is an important communication channel that can help hospitals and consumers obtain feedback about quality of care. However, despite the potential value of insight from consumers who post comments about hospital care on social media, there has been little empirical research on the relationship between patients' anecdotal feedback and formal measures of patient experience. The aim of the study was to test the association between informal feedback posted in the Reviews section of hospitals' Facebook pages and scores on two global items from the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, Overall Hospital Rating and Willingness to Recommend the Hospital. We retrieved star ratings and anecdotal comments posted in Reviews sections of 131 hospitals' Facebook pages. Using a machine learning algorithm, we analyzed 57,985 comments to measure consumers' sentiment about the hospitals. We used regression analysis to determine whether consumers' quantitative and qualitative postings would predict global measures from the HCAHPS survey. Both number of stars and the number of positive comments posted on hospitals' Facebook Reviews sections were associated with higher overall ratings and willingness to recommend the hospital. The findings suggest that patients' informal comments help predict a hospital's formal measures of patient experience. Consistent with crowd wisdom, ordinary consumers may have valid insights that can help others to assess patient experience at a hospital. Given that some people will judge hospital quality based on opinions voiced in social media, further research should continue to explore associations between anecdotal commentary and a variety of quality indicators. Administrators can tap into the wealth of commentary on social media as the forum continues to expand its influence in health care. Comments on social media may also serve as an early snapshot of patient-reported experiences, alerting

  5. 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.

  6. La publicidad de lo íntimo. El Epistolario Sentimental de la revista Para Ti [1924-1933

    OpenAIRE

    Paula Bontempo

    2011-01-01

    Para Ti, el semanario femenino de Editorial Atlántida apareció en el mercado en 1922 como una revista de servicios multipropósitos. El presente artículo se propone estudiar el Epistolario Sentimental, columna que intentaba dar respuesta a los conflictos del corazón. Esta sección constituyó un lugar para hablar de temas que en el resto de la revista no se trataban. Así, la sexualidad, la sensualidad, los deseos y los conflictos familiares ingresaron en el mundo de Para Ti y de su público a tra...

  7. “My Invisalign experience”: content, metrics and comment sentiment analysis of the most popular patient testimonials on YouTube

    Directory of Open Access Journals (Sweden)

    Christos Livas

    2018-01-01

    Full Text Available Abstract Background The aim of the study was to investigate the popularity, content of Invisalign patient testimonials on YouTube, as well as the sentiment of the related comments. Methods Using the term “Invisalign experience,” the top 100 results on YouTube by view count were screened for English spoken patient videos that attracted comments. Video information (time since video upload, sponsorship, engagement metrics (comments, likes, dislikes, subscriptions, and views were collected. Videos were rated for information completeness (ICS, and comments were classified by origin and content. The emotional loading of the comments was measured using automated sentiment analysis. Results The 40 reviewed testimonials scored an average ICS of 3.78 (SD 0.97. ICS, time since upload, and video duration did not appear to significantly influence the number of views, subscriptions, likes, dislikes, and comments. There was a statistically significant difference (P = 0.03 between mean positive (2.01, SD 0.95 and negative sentiment scores (− 1.90, SD 1.14. Commenter’s status and overall comment on video were significantly associated with positive sentiment scores. There was a significant association between sponsorship, commenter’s status, overall comment on video, focus of concern, perceived Invisalign’s disadvantages, and increased negative sentiment scores. Conclusions Engagement of audience and views of the most popular Invisalign patient testimonials were not significantly influenced by completeness of information, video duration, and lifespan. The sentiment of viewers’ comments about Invisalign treatment was significantly more positive and was significantly associated with their status, content, and sponsorship of videos. Orthodontic trends on YouTube need to be cautiously monitored for planning interventions that improve patients’ knowledge about orthodontics.

  8. Suicides as a response to adverse market sentiment (1980-2016.

    Directory of Open Access Journals (Sweden)

    Pankaj Agrrawal

    Full Text Available Financial crises inflict significant human as well as economic hardship. This paper focuses on the human fallout of capital market stress. Financial stress-induced behavioral changes can manifest in higher suicide and murder-suicide rates. We find that these rates also correlate with the Gross Domestic Product (GDP growth rate (negatively associated; a -0.25% drop [in the rate of change in annual suicides for a +1% change in the independent variable], unemployment rate (positive link; 0.298% increase, inflation rate (positive link; 0.169% increase in suicide rate levels and stock market returns adjusted for the risk-free T-Bill rate (negative link; -0.047% drop. Suicides tend to rise during periods of economic turmoil, such as the recent Great Recession of 2008. An analysis of Centers for Disease Control and Prevention (CDC data of more than 2 million non-natural deaths in the US since 1980 reveals a positive correlation with unemployment levels. We find that suicides and murder-suicides associated with adverse market sentiment lag the initial stressor by up to two years, thus opening a policy window for government/public health intervention to reduce these negative outcomes. Both our models explain about 73 to 76% of the variance in suicide rates and rate of change in suicide rates, and deploy a total of four widely available independent variables (lagged and/or transformed. The results are invariant to the inclusion/exclusion of 2008 data over the 1980-2016 time series, the period of our study. The disconnect between rational decision making, induced by cognitive dissonance and severe financial stress can lead to suboptimal outcomes, not only in the area of investing, but in a direct loss of human capital. No economic system can afford such losses. Finance journal articles focus on monetary alpha, which is the return on a portfolio in excess of the benchmark; we think it is important to be aware of the loss of human capital as a consequence of

  9. Suicides as a response to adverse market sentiment (1980-2016).

    Science.gov (United States)

    Agrrawal, Pankaj; Waggle, Doug; Sandweiss, Daniel H

    2017-01-01

    Financial crises inflict significant human as well as economic hardship. This paper focuses on the human fallout of capital market stress. Financial stress-induced behavioral changes can manifest in higher suicide and murder-suicide rates. We find that these rates also correlate with the Gross Domestic Product (GDP) growth rate (negatively associated; a -0.25% drop [in the rate of change in annual suicides for a +1% change in the independent variable]), unemployment rate (positive link; 0.298% increase), inflation rate (positive link; 0.169% increase in suicide rate levels) and stock market returns adjusted for the risk-free T-Bill rate (negative link; -0.047% drop). Suicides tend to rise during periods of economic turmoil, such as the recent Great Recession of 2008. An analysis of Centers for Disease Control and Prevention (CDC) data of more than 2 million non-natural deaths in the US since 1980 reveals a positive correlation with unemployment levels. We find that suicides and murder-suicides associated with adverse market sentiment lag the initial stressor by up to two years, thus opening a policy window for government/public health intervention to reduce these negative outcomes. Both our models explain about 73 to 76% of the variance in suicide rates and rate of change in suicide rates, and deploy a total of four widely available independent variables (lagged and/or transformed). The results are invariant to the inclusion/exclusion of 2008 data over the 1980-2016 time series, the period of our study. The disconnect between rational decision making, induced by cognitive dissonance and severe financial stress can lead to suboptimal outcomes, not only in the area of investing, but in a direct loss of human capital. No economic system can afford such losses. Finance journal articles focus on monetary alpha, which is the return on a portfolio in excess of the benchmark; we think it is important to be aware of the loss of human capital as a consequence of market

  10. 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.

  11. The sentiments of love and aspirations for marriage and their association with teenage sexual activity and pregnancy.

    Science.gov (United States)

    Scott, J W

    1983-01-01

    This study questions the findings of most research claiming that teenage pregnancies are generally unwanted, unplanned and unintended. It starts with the question of why most sexually active teenagers put themselves at risk of becoming pregnant if they do not desire it. The hypothesis is that sentiments of "love" and "aspirations for marriage" are related to starting sexual activity and subsequent pregnancy. The sample is 123 school-age mothers. It was found that sentiments of "love" were associated with becoming pregnant more than with starting sexual activity. Most of the respondents who were "in love" at the onset of pregnancy were hoping to marry their sex partners and, in fact, many thought that marriage would occur in the very near future following the outcome of pregnancy. These findings suggest that more research needs to be directed at the development of affective bonds with and the aspirations for marriage to the sex partners. Such research may explain why these teenagers put themselves at risk.

  12. 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%.

  13. 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.

  14. 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.

  15. A construção da heroína “romântica”: educação sentimental em “Miss Dollar”, de Machado de Assis

    OpenAIRE

    Pereira, Cilene Margarete

    2010-01-01

    This article analyzes the aspects of composition of the main feminine character of the short story “Miss Dollar”, by Machado de Assis, arguing the role of literature for the sentimental formation of the machadian woman. Este artigo analisa os aspectos de composição da principal personagem feminina do conto “Miss Dollar”, de Machado de Assis, discutindo o papel da literatura para a formação sentimental da mulher machadiana.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  18. 'Nothing is so soon forgot as pain': Reading Agony in Adam Smith's The Theory of Moral Sentiments.

    Science.gov (United States)

    Franson, Craig

    2014-01-01

    Giving a rigorous philosophical explanation to the imagination's role in sympathy, Adam Smith's The Theory of Moral Sentiments became a central text in Romantic aesthetics. It not only justified the age's vogue for making suffering an object of artistic pleasure, it treated suffering's affectivity as the very foundation of society. Depicting agony as a spectacle to be read by others, Smith transformed morality into rhetoric, making human subjects into readers of a sentimentalised, textual world. Yet Smith's work restricted the bonds of sympathy, too, following established distinctions between mind and body that helped him to exclude physical pain from sympathetic response. This essay looks to Smith's context in the overlapping philosophical and medical discourses of the Scottish Enlightenment, exploring his moral theory's resonance with the nerve theories of Robert Whytt and William Cullen, then the leading figures in Scotland's rising medical community. Deepening our understanding of Smith's probable sources, it reframes Smith's intellectual and ideological legacy, foregrounding some of the ambivalent cultural and political implications of Smith's troubling censure of physical pain.

  19. Does morality have a biological basis? An empirical test of the factors governing moral sentiments relating to incest.

    Science.gov (United States)

    Lieberman, Debra; Tooby, John; Cosmides, Leda

    2003-04-22

    Kin-recognition systems have been hypothesized to exist in humans, and adaptively to regulate altruism and incest avoidance among close genetic kin. This latter function allows the architecture of the kin recognition system to be mapped by quantitatively matching individual variation in opposition to incest to individual variation in developmental parameters, such as family structure and co-residence patterns. Methodological difficulties that appear when subjects are asked to disclose incestuous inclinations can be circumvented by measuring their opposition to incest in third parties, i.e. morality. This method allows a direct test of Westermarck's original hypothesis that childhood co-residence with an opposite-sex individual predicts the strength of moral sentiments regarding third-party sibling incest. Results support Westermarck's hypothesis and the model of kin recognition that it implies. Co-residence duration objectively predicts genetic relatedness, making it a reliable cue to kinship. Co-residence duration predicts the strength of opposition to incest, even after controlling for relatedness and even when co-residing individuals are genetically unrelated. This undercuts kin-recognition models requiring matching to self (through, for example, major histocompatibility complex or phenotypic markers). Subjects' beliefs about relatedness had no effect after controlling for co-residence, indicating that systems regulating kin-relevant behaviours are non-conscious, and calibrated by co-residence, not belief.

  20. Monitoring the environment and human sentiment on the Great Barrier Reef: Assessing the potential of collective sensing.

    Science.gov (United States)

    Becken, Susanne; Stantic, Bela; Chen, Jinyan; Alaei, Ali Reza; Connolly, Rod M

    2017-12-01

    With the growth of smartphone usage the number of social media posts has significantly increased and represents potentially valuable information for management, including of natural resources and the environment. Already, evidence of using 'human sensor' in crises management suggests that collective knowledge could be used to complement traditional monitoring. This research uses Twitter data posted from the Great Barrier Reef region, Australia, to assess whether the extent and type of data could be used to Great Barrier Reef organisations as part of their monitoring program. The analysis reveals that large amounts of tweets, covering the geographic area of interest, are available and that the pool of information providers is greatly enhanced by the large number of tourists to this region. A keyword and sentiment analysis demonstrates the usefulness of the Twitter data, but also highlights that the actual number of Reef-related tweets is comparatively small and lacks specificity. Suggestions for further steps towards the development of an integrative data platform that incorporates social media are provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Public Response to Scientific Misconduct: Assessing Changes in Public Sentiment Toward the Stimulus-Triggered Acquisition of Pluripotency (STAP) Cell Case via Twitter.

    Science.gov (United States)

    Gayle, Alberto; Shimaoka, Motomu

    2017-04-20

    In this age of social media, any news-good or bad-has the potential to spread in unpredictable ways. Changes in public sentiment have the potential to either drive or limit investment in publicly funded activities, such as scientific research. As a result, understanding the ways in which reported cases of scientific misconduct shape public sentiment is becoming increasingly essential-for researchers and institutions, as well as for policy makers and funders. In this study, we thus set out to assess and define the patterns according to which public sentiment may change in response to reported cases of scientific misconduct. This study focuses on the public response to the events involved in a recent case of major scientific misconduct that occurred in 2014 in Japan-stimulus-triggered acquisition of pluripotency (STAP) cell case. The aims of this study were to determine (1) the patterns according to which public sentiment changes in response to scientific misconduct; (2) whether such measures vary significantly, coincident with major timeline events; and (3) whether the changes observed mirror the response patterns reported in the literature with respect to other classes of events, such as entertainment news and disaster reports. The recent STAP cell scandal is used as a test case. Changes in the volume and polarity of discussion were assessed using a sampling of case-related Twitter data, published between January 28, 2014 and March 15, 2015. Rapidminer was used for text processing and the popular bag-of-words algorithm, SentiWordNet, was used in Rapidminer to calculate sentiment for each sample Tweet. Relative volume and sentiment was then assessed overall, month-to-month, and with respect to individual entities. Despite the ostensibly negative subject, average sentiment over the observed period tended to be neutral (-0.04); however, a notable downward trend (y=-0.01 x +0.09; R ²=.45) was observed month-to-month. Notably polarized tweets accounted for less than

  2. “When ‘Bad’ is ‘Good’”: Identifying Personal Communication and Sentiment in Drug-Related Tweets

    Science.gov (United States)

    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) expressed in cannabis- and synthetic cannabinoid–related tweets. Methods 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

  3. Explaining Anti-U.S. Military Base Sentiment in South Korea

    Science.gov (United States)

    2017-06-01

    the U.S. vessel for encroaching its water territory. All 83 U.S Navy personnel held for hostage and released after almost a year in prison camp...the ruling government was unpermitted and punishable under the National Security Act 1948. Moreover, the anti- U.S. military base phenomenon was

  4. Negation handling in sentiment classification using rule-based adapted from Indonesian language syntactic for Indonesian text in Twitter

    Science.gov (United States)

    Amalia, Rizkiana; Arif Bijaksana, Moch; Darmantoro, Dhinta

    2018-03-01

    The presence of the word negation is able to change the polarity of the text if it is not handled properly it will affect the performance of the sentiment classification. Negation words in Indonesian are ‘tidak’, ‘bukan’, ‘belum’ and ‘jangan’. Also, there is a conjunction word that able to reverse the actual values, as the word ‘tetapi’, or ‘tapi’. Unigram has shortcomings in dealing with the existence of negation because it treats negation word and the negated words as separate words. A general approach for negation handling in English text gives the tag ‘NEG_’ for following words after negation until the first punctuation. But this may gives the tag to un-negated, and this approach does not handle negation and conjunction in one sentences. The rule-based method to determine what words negated by adapting the rules of Indonesian language syntactic of negation to determine the scope of negation was proposed in this study. With adapting syntactic rules and tagging “NEG_” using SVM classifier with RBF kernel has better performance results than the other experiments. Considering the average F1-score value, the performance of this proposed method can be improved against baseline equal to 1.79% (baseline without negation handling) and 5% (baseline with existing negation handling) for a dataset that all tweets contain negation words. And also for the second dataset that has the various number of negation words in document tweet. It can be improved against baseline at 2.69% (without negation handling) and 3.17% (with existing negation handling).

  5. Violencia de género y procesos de empobrecimiento: estudio de la violencia contra las mujeres por parte de su pareja o ex-pareja sentimental

    OpenAIRE

    Espinar-Ruiz, Eva

    2003-01-01

    El objetivo de esta investigación ha sido analizar las posibles relaciones entre la violencia de la que puede ser objeto una mujer por parte de su pareja o ex-pareja sentimental y diferentes procesos de empobrecimiento. Para ello, aplicando un enfoque de género, se atiende a dos perspectivas: los procesos de empobrecimiento como contexto en el que pueden tener lugar situaciones de violencia y la propia violencia como factor de empobrecimiento. La estrategia metodológica seguida es básic...

  6. La figure de Zidane et le sentiment d’appartenance communautaire des deux côtés du Rhin

    OpenAIRE

    Tietze, Nikola

    2013-01-01

    En tant que figure emblématique de la grandeur du football, Zinedine Zidane permet d’établir une approche sociologique de la construction d’un sentiment d’appartenance sub et transnational. C’est ce qui se dégage de déclarations faites à Berlin, à Hambourg, à Paris et à Lyon par des musulmans, des Kabyles et des Palestiniens. Ces personnes ont été interviewées sur la manière dont elles conçoivent la communauté comme bien commun dans son opposition critique au contexte social et politique. Aut...

  7. Le Sentiment de la solitude dans Ourika de Mme de Duras ou l'Héroïde réinventée

    OpenAIRE

    Langle, Catherine

    2011-01-01

    International audience; Cette étude traite du sentiment de !a solitude dont l'héroïne, Ourika fait état, et qui, au-delà de son assignation à des causes sociopolitiques, demeure énigmatique. Le témoignage de L'ancienne esclave constitue la substance même du roman : celui-ci montre les répercussions subjectives d 'une situation d'exclusion qui tient à une rigidité des structures sociales déterminant La polarisation des esprits sur un trait du visible : une peau noire. Mais le " noir " , déclin...

  8. Hate Speech or Genocidal Discourse? An Examination of Anti-Roma Sentiment in Contemporary Europe

    Directory of Open Access Journals (Sweden)

    Emma Townsend

    2014-08-01

    Full Text Available Roma in contemporary Europe are the frequent targets of hate speech and discriminatory state policies. Despite being the largest minority in the European Union with a population of 10-12 million, they are frequently denied a space in European society, and are widely perceived to be unchangeable and inherently ‘other’. As a result, Roma experience substantially inferior life conditions when compared to majority European populations. Despite the many recent European Union initiatives and action plans, such as the Decade of Roma Inclusion (2005-2015, the situation of Roma in contemporary Europe is not improving, and in some cases is actually worsening. This persecution is not a modern phenomenon; Roma have suffered stigmatisation and exclusion throughout their history in Europe. The severity and continuity of the persecution of Roma at the hands of a multitude of European authorities suggests the presence of an underlying motivation or intent that informs both the rhetoric about and treatment of Romani people. This paper will examine if the persecution of Roma in contemporary Europe is guided by a genocidal discourse. To this end, the boundaries between hate speech, genocidal discourse, and incitement to genocide will be scrutinised. It will be argued that both the way the Roma are spoken about and the treatment they receive are informed by a genocidal discourse that has endured relatively unchanged throughout their history in Europe. Roma are not just racially vilified, rather their culture as well as their physical presence in contemporary Europe are widely devalued in both words and in state action. Any improvement in their situation is therefore unlikely while this discourse continues.

  9. 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

  10. 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.

  11. Nostalgia and Consumer Sentiment.

    Science.gov (United States)

    Moriarty, Sandra Ernst; McGann, Anthony F.

    1983-01-01

    Concludes that designer magazine advertisements contain more traces of nostalgia than do those in consumer magazines and that they tend to be more extreme in their fluctuation patterns. Notes that nostalgia increases in ads when public confidence is decreasing. (FL)

  12. General Sentiment and Value

    DEFF Research Database (Denmark)

    Arvidsson, Adam; Etter, Michael; Colleoni, Elanor

    The aim of this paper is to deepen the understanding of the relationship between corporate reputation and financial value. Theories as the resource based view or the contractual view lie ground for the assumption of a linear positive correlation between reputation and financial performance. However...

  13. Pequeños defectos que debemos corregir: aprendiendo a ser mujer en la historieta sentimental de los años cincuenta y sesenta

    Directory of Open Access Journals (Sweden)

    Jiménez Morales, Rosario

    2011-09-01

    Full Text Available The so called “sentimental story” published in the 40s and 50s in Spain played an important part in women education during the postwar period. Publications as Florita, Mariló or Blanca spread a symbolic construction of feminity based on submissiveness. Love was the only destiny for women. And therefore they had to prepare themselves for it. Values as simplicity, integrity, absolute devotion to men and to the family, and rejection of fantasy represented the axiology of this publications. Feminine comic perpetuated in this way the asymetric relationships in the Spanish society at the time by using a process sometimes even autorreferential since this reductionist image was created and disseminated by women authors as well.

    La historieta sentimental de los años cuarenta y cincuenta jugó un papel fundamental en la educación de la mujer durante la época de la posguerra en España. Publicaciones como Florita, Mariló o Blanca difundían una construcción simbólica de la feminidad basada en la sumisión. La mujer era el sujeto destinado al amor y debía prepararse para ese final único. Valores como la sencillez, la honradez, la entrega absoluta al hombre y a la familia y el rechazo de la fantasía constituían la axiología de estas publicaciones. De esta forma, el cómic femenino perpetuaba las relaciones asimétricas de poder presentes en la sociedad española de la época mediante un proceso en ocasiones autorreferencial, ya que fueron muchas las autoras que colaboraron en la difusión de esta imagen reduccionista.

  14. Anti-Muslim Sentiments and Violence: A Major Threat to Ethnic Reconciliation and Ethnic Harmony in Post-War Sri Lanka

    Directory of Open Access Journals (Sweden)

    Athambawa Sarjoon

    2016-10-01

    Full Text Available Following the military defeat of LTTE terrorism in May 2009, the relationship between ethnic and religious groups in Sri Lanka became seriously fragmented as a result of intensified anti-minority sentiments and violence. Consequently, the ethnic Muslims (Moors became the major target in this conflict. The major objective of this study is to critically evaluate the nature and the impact of the anti-Muslim sentiments expressed and violence committed by the extreme nationalist forces during the process of ethnic reconciliation in post-war Sri Lanka. The findings of the study reveal that, with the end of civil war, Muslims have become “another other” and also the target of ethno-religious hatred and violence from the vigilante right-wing ethno-nationalist forces that claim to be protecting the Sinhala-Buddhist nation, race, and culture in Sri Lanka. These acts are perpetrated as part of their tactics aimed to consolidate a strong Sinhala-Buddhist nation—and motivated by the state. Furthermore, the recourse deficit and lack of autonomy within the organizational hierarchy of the Buddhist clergy have motivated the nationalist monks to engage in politics and promote a radical anti-minority rhetoric. This study recommends institutional and procedural reforms to guide and monitor the activities of religious organizations, parties, and movements, together with the teaching of religious tolerance, as the preconditions for ethnic reconciliation and ethnic harmony in post-war Sri Lanka. This study has used only secondary data, which are analyzed in a descriptive and interpretive manner.

  15. Under Under Under / Merit Kask

    Index Scriptorium Estoniae

    Kask, Merit

    2006-01-01

    20. nov. esietendub Kumu auditooriumis MTÜ Ühenduse R.A.A.A.M teatriprojekt "Under" poetess Marie Underist. Lavastajad Merle Karusoo ja Raimo Pass, kunstnik Jaagup Roomet, helilooja Urmas Lattikas, peaosas Katrin Saukas

  16. La influencia de la comedia sentimental en la poética del drama histórico y de la tragedia neoclásica a principios del siglo XIX en España

    OpenAIRE

    Coca Ramírez, Fátima

    2000-01-01

    En nuestro trabajo analizamos la influencia de la filosofía sensualista y del género de la comedia sentimental en la concepción del nuevo drama histórico del romanticismo por un lado, y en el cambio de concepción del género clásico de la tragedia, por otra; atendiendo a las primeras preceptivas poéticas de los inicios del siglo XIX español.

  17. When a new technological product launching fails: A multi-method approach of facial recognition and E-WOM sentiment analysis.

    Science.gov (United States)

    Hernández-Fernández, Dra Asunción; Mora, Elísabet; Vizcaíno Hernández, María Isabel

    2018-04-17

    The dual aim of this research is, firstly, to analyze the physiological and unconscious emotional response of consumers to a new technological product and, secondly, link this emotional response to consumer conscious verbal reports of positive and negative product perceptions. In order to do this, biometrics and self-reported measures of emotional response are combined. On the one hand, a neuromarketing experiment based on the facial recognition of emotions of 10 subjects, when physical attributes and economic information of a technological product are exposed, shows the prevalence of the ambivalent emotion of surprise. On the other hand, a nethnographic qualitative approach of sentiment analysis of 67-user online comments characterise the valence of this emotion as mainly negative in the case and context studied. Theoretical, practical and methodological contributions are anticipated from this paper. From a theoretical point of view this proposal contributes valuable information to the product design process, to an effective development of the marketing mix variables of price and promotion, and to a successful selection of the target market. From a practical point of view, the approach employed in the case study on the product Google Glass provides empirical evidence useful in the decision making process for this and other technological enterprises launching a new product. And from a methodological point of view, the usefulness of integrated neuromarketing-eWOM analysis could contribute to the proliferation of this tandem in marketing research. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. The Part of the Whole: Analysis of the Relationship between the European Cultural Model, the „Sentiment of Being”, and the Structures of Language

    Directory of Open Access Journals (Sweden)

    Bilba Corneliu

    2005-06-01

    Full Text Available In this paper I attempt to sketch out a critique of Constantin Noica’s notion of cultural model. In his writings on this topic, the Romanian philosopher articulates an atemporal typology of culture which is based on five types of relationship between rule and exception, or between the One and the Many. In this semantic context I set out to show that the five relations between the One and the Many are in fact ways of conceiving the relationship between man and being, and, furthermore, that in times past, culture (or the relationship between man and being was structured by religion. Noica approaches this issue from a modern perspective, according to which religion is one of the many domains of culture, the coherence and structure of which was derived from an abstract scheme. This kind of approach cannot yield the expected result. Thus, according to Noica, the ancient monotheistic culture, for instance, was structured by the fundamental fact that the „exception confirms the rule.” Against this interpretation, I attempt to show that Noica’s scheme of cultural explanation has little if any value unless it is applied to a culture which is endowed with the sentiment that it has an exceptional destiny. More specifically, monotheistic religion in the ancient world is the exception to a broader rule. The practitioners of monotheistic religion highlight their difference and exceptional condition, which is precisely that which makes it possible for the exception to confirm the rule. This proves that the types of relations that establish between the One and the Many are meaningless in the absence of their material conditioning. On the other hand, Noica tries to articulate a new cultural morphology from the standpoint of grammatical morphology. His attempt yields a typology of European culture based on the idea that each of the familiar historical periods (the Medieval Age, The Renaissance, the Baroque, the Enlightenment, Romanticism, and late

  19. 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

  20. S’auto évaluer pour agir : rôle du sentiment d’efficacité personnelle dans les pratiques d’enseignement

    Directory of Open Access Journals (Sweden)

    Sandra Safourcade

    2011-01-01

    Full Text Available Dans son quotidien, l’enseignant est amené à prendre des décisions, évaluer les éléments favorables du contexte, mobiliser des ressources afin d’organiser l’activité pédagogique. L’ensemble de ces choix tactiques ou stratégiques est sous-tendu par un processus d’auto-évaluation de son action que nous avons souhaité analyser. Au sein du collège les enseignants vivent en direct la nécessaire adaptation de leur projet pédagogique à la spécificité des élèves et à la différenciation de leurs actes. Ces enseignants, entre deux rives, ont au quotidien à la fois, à conduire leur activité, à auto évaluer celle-ci et à construire des pratiques efficaces. Notre recherche nous permet de décrire et d’expliquer le rôle des processus internes d’auto-évaluation des actions professionnelles. Ces procédures sont en interaction avec la construction chez l’enseignant d’un sentiment d’auto-efficacité qui, au-delà de renforcer l’estime de soi, est un véritable moteur de la valorisation et de la production des actes d’enseignement.In their day to day work, teachers are required to make decisions, evaluate the positive elements in their environment and mobilize resources in order to organize their pedagogical activity. All of these tactical or strategic choices are underlain by a self-evaluation process of their action that we have chosen to analyze. In junior high school, teachers get to see how it is necessary to adapt their pedagogical projects to students’ specificity and to differentiated acts. Daily, these teachers have, at the same time, to conduct their activity, to self-evaluate it and to conceive efficient practices. This study enables us to better describe and explain the role of internal self-assessment processes of professional actions. These self-evaluation processes interact with the building of a sense of efficiency that, beyond strengthening teachers’ self-esteem, is a true engine of

  1. Città, violenza urbana e sentimento di insicurezza / Villes, violence urbaine et sentiment d’insécurité / Cities, urban violence and insecurity

    Directory of Open Access Journals (Sweden)

    Lourenço Nelson

    2012-10-01

    Full Text Available Cet article met en évidence que la violence urbaine et l’insécurité sont des thèmes centraux pour les sociétés actuelles car ils font partie des préoccupations de la population et de la vie démocratique de manière significative. Pour aborder cette problématique, il est nécessaire d’effectuer une analyse extensive de la mondialisation et des dynamiques urbaines qui caractérisent la fin de l’époque moderne dans ses multiples dimensions, par exemple sociales, culturelles et politiques. Violence urbaine et insécurité demandent une structure institutionnelle nouvelle et la définition de politiques publiques de sécurité nouvelles pour répondre à l’insécurité qui domine dans les sociétés urbaines.L’analyse globale des relations entre l’évolution de la criminalité et le développement du sentiment d’insécurité amène l’auteur à expliquer la manière dont les sociétés contemporaines vivent et abordent la question de la sécurité. This paper argues that urban violence and insecurity are central societal issues which are a significant part of people's concerns and democratic life. Its analysis implies an extensive understanding of globalisation and urban dynamics that characterise late modernity in its multiple dimensions: i.e. the social, cultural, political, and economical dimensions.Urban violence and insecurity call for a new institutional framework and the definition of new public security policies that will respond to the insecurity that prevails in urban society.The comprehensive analysis of the relationship between the evolution of crime and the development of the feeling of insecurity allows us to understand how contemporary society lives and deals with the issue of security.

  2. Popular Sentiments and Public Executions

    Directory of Open Access Journals (Sweden)

    Gail Marshall

    2011-09-01

    Full Text Available This paper examines Dickens’s descriptions of public executions in his letters and early journalism as a context in which to read the final scene of 'A Tale of Two Cities' (1859. It argues that despite his traumatised responses to public hangings, Dickens is able to use the site of the scaffold to articulate some fundamental human fears and dispositions. The paper compares Dickens’s response to the horrors of the French Revolution with Carlyle’s, and shows throughout how Dickens firmly repudiates Trollope's somewhat rueful dismissal of him as ‘Mr Popular Sentiment’.

  3. Querying Sentiment Development over Time

    DEFF Research Database (Denmark)

    Andreasen, Troels; Christiansen, Henning; Have, Christian Theil

    2013-01-01

    that measures how well a hypothesis characterizes a given time interval; the semantics is parameterized so it can be adjusted to different views of the data. EmoEpisodes is extended to a query language with variables standing for unknown topics and emotions, and the query-answering mechanism will return...

  4. Querying Sentiment Development over Time

    DEFF Research Database (Denmark)

    Andreasen, Troels; Christiansen, Henning; Have, Christian Theil

    2013-01-01

    A new language is introduced for describing hypotheses about fluctuations of measurable properties in streams of timestamped data, and as prime example, we consider trends of emotions in the constantly flowing stream of Twitter messages. The language, called EmoEpisodes, has a precise semantics...... that measures how well a hypothesis characterizes a given time interval; the semantics is parameterized so it can be adjusted to different views of the data. EmoEpisodes is extended to a query language with variables standing for unknown topics and emotions, and the query-answering mechanism will return...... instantiations for topics and emotions as well as time intervals that provide the largest deflections in this measurement. Experiments are performed on a selection of Twitter data to demonstrates the usefulness of the approach....

  5. La traducción de las escritoras inglesas y la novela española del primer tercio del siglo XIX: lo histórico, lo sentimental y lo gótico

    Directory of Open Access Journals (Sweden)

    Establier Pérez, Helena

    2010-06-01

    Full Text Available Though women writing was presenting in the England of the first third of century XIX a considerable development and a maturity, the certain thing is that the list of British novelists whose works arrive at that same time at our country is limited enough. All these texts —translated into Spanish in the same dates, the second and the third decades of the century— are framed inside popular genres, with great presence of didactism and sentimentalism, elements derived from the adventures of the heroic narrative and ingredients of Gothic romances. This paper focuses in the scarce translations from English women’s novels presenting elements and narrative techniques characteristic of Gothic tales, a genre very inusual in Spain at the beginning os XIXth century, specifically the works of Sophia Lee, Regina Maria Roche and Ann Radcliffe. Its presence in the Spanish literary panorama of the first third of XIXth. Century reveals the publishing demands of a new public, more and more bourgeois and feminine, eager to consume the readings that entertained the European middle-class of his time and to have access to women writing, as much in the didactic and sentimental field like in the Gothic novel.Aunque la escritura de las mujeres presentaba en la Inglaterra del primer tercio del siglo XIX un desarrollo y una madurez considerables, lo cierto es que la lista de novelistas británicas cuyas obras llegan en esa misma época a nuestro país es bastante reducida. Todos estos textos —que en conjunto no superan la veintena y que se traducen al español en las mismas fechas, la segunda y la tercera décadas del siglo— se enmarcan dentro de géneros populares, con gran presencia del didactismo y de lo sentimental, elementos derivados de las aventuras de la narrativa heroica e ingredientes del relato gótico que destacan sobre el fondo social costumbrista de la novela inglesa dieciochesca. Este trabajo se centra fundamentalmente en las escasas traducciones de

  6. L’esport com a instrument reforçador del sentiment nacional. Les implicacions dels triomfs de la selecció espanyola de futbol en el discurs de la militància valenciana d’esquerra i centreesquerra

    Directory of Open Access Journals (Sweden)

    Lluís Català Oltra

    2013-12-01

    Full Text Available En aquest treball es repassa primerament el paper que ha tingut l’esport en el reforçament de la identitat nacional. A continuació, centrem l’atenció en el futbol per a parlar de la dinàmica centre-perifèria duta al terreny dels clubs de la Lliga espanyola; i dels èxits de la selecció espanyola i les implicacions per al sentiment nacional. Això últim ens serveix de base per a l’estudi empíric desenvolupat a partir d’entrevistes semiestructurades a militants de base de partits valencians d’esquerra i centreesquerra. Amb aquest material analitzem els discursos dels militants sobre aquestes victòries i la seua relació amb la identitat nacional. | In this work firstly we review the role played by the sport in the reinforcement of national identity. Next, we focus on the football, to talk about the centre-periphery dynamic brought to the terrain of Spanish League clubs; and about the successes of the Spanish national team and their implications for the national feeling. This last serves us as a base for the empirical study developed from semistructured interviews to militants of left-wing and centre-left-wing Valencian parties. With this material we analyse the discourses of the militants about these victories and their relation with national identity.

  7. 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

  8. Sentiment analysis on tweets for social events

    DEFF Research Database (Denmark)

    Zhou, Xujuan; Tao, Xiaohui; Yong, Jianming

    2013-01-01

    , 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...... political candidates, i.e., two primary minister candidates - Julia Gillard and Tony Abbot. Our experimental results demonstrate the effectiveness of the system....

  9. Daily Market News Sentiment and Stock Prices

    NARCIS (Netherlands)

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

    2015-01-01

    textabstractIn recent years there has been a tremendous growth in the influx of news related to traded assets in international financial markets. This financial news is now available via print media but also through real-time online sources such as internet news and social media sources. The

  10. Sex and sentiment in Cuban tourism.

    Science.gov (United States)

    Babb, Florence E

    2010-01-01

    Helen Safa has been a leading program builder and pioneer in research that examines the complex intersections of gender, race, class, and nation in Latin America and the Caribbean. Her comparative research culminated in her influential book, The Myth of the Male Breadwinner: Women and Industrialization in the Caribbean (1995), which examined gender, family, and employment across three Caribbean societies. Over several decades Safa has inspired scholarship throughout the Caribbean and the Americas and her work is exemplary of engaged anthropology in the region. Here I present work I conducted in Cuba that was guided, like my work in Peru, Nicaragua, and southern Mexico by the writings of Safa and others who saw the critical need to bring gender into meaningful discussion in the field of Latin American and Caribbean studies. In what follows, drawn from my broader research on tourism in four nations, I explore and reflect on the contemporary dynamics of sex and romance tourism in Cuba. I suggest that the allure of this domain of tourism may be enhanced by Cuba's global political identity, and that Cuban women participating in commodified and intimate exchanges reveal an ability to get along in a market economy that generally excludes them.

  11. Latent Dirichlet Markov allocation for sentiment analysis

    NARCIS (Netherlands)

    Bagheri, Ayoub; Saraee, Mohamad; de Jong, Franciska M.G.

    In recent years probabilistic topic models have gained tremendous attention in data mining and natural language processing research areas. In the field of information retrieval for text mining, a variety of probabilistic topic models have been used to analyse content of documents. A topic model is a

  12. Le roman anglais du XVIIIe siècle à l’opéra : la sentimentalité, Pamela et The Maid of the Mill The 18th-century Novel as Opera: Sentimentality, Pamela and The Maid of the Mill

    Directory of Open Access Journals (Sweden)

    Michael Burden

    2011-12-01

    Full Text Available Cet article revient sur la notion de sentimentalité et particulièrement sur l’opéra sentimental qui dérive du roman anglais de même nature. L’idée du triomphe ultime du bien, de la possibilité pour une jeune fille pauvre mais honnête de réussir dans la vie et de la bonté comme lien inaltérable unissant les hommes acquit une telle force à la fin du XVIIIe siècle qu’elle a été utilisée pour la définir. Une des œuvres les plus significatives du style sentimental, Pamela, le roman de Richardson, retint l’attention du librettiste Isaac Bickerstaffe (1733-1808, qui le transforma en « opéra anglais » faisant remarquer que son œuvre, « une bagatelle à bien des points de vue, constituait la première pièce sentimentale qui paraisse sur la scène anglaise depuis 40 ans ». Mis en musique par Samuel Arnold (1740-1802 l’opéra présente un genre nouveau, « l’opéra pastiche », qui incorpore la musique de plusieurs compositeurs. Musicalement, l’opéra n’a rien de très original et selon nos critères actuels, l’absence d’un seul compositeur nettement identifiable ou d’une esthétique de composition particulière en fait un objet d’art difficile à jauger. Mais la simplicité de  la musique elle-même constitue un attribut essentiel qui permet à la sentimentalité de l’histoire de s’exprimer et annonce véritablement la naissance d’un nouveau genre d’opéra anglais, le pastiche. De même, les caractéristiques très particulières des représentations théâtrales en Angleterre ont joué un rôle déterminant dans le développement de l’opéra sentimental à Londres.This article returns to the well-known notion of sentimental culture, and specifically, to sentimental opera derived from the English novel.  The notion that goodness must triumph, that a poor but honest girl should ‘make good’, and that such goodness should form a binding force between humans, was such a strong force in

  13. Applying for a New Paradigm. Not Anti-globalization, but Alter-globalization?

    Directory of Open Access Journals (Sweden)

    Dan Popescu

    2007-08-01

    Full Text Available the alter-globalization opposed not only to the present globalization but also toanti-globalization.Why? Which are the essential arguments in this direction, what does the alter-globalization rely on,as well as its criticism in the field of present day globalization? Why is it often stated that alter globalizationcan constitute a component in the building of a new paradigm that our world however needs somuch?These are the questions our article is trying to answer underlining a Romanian point of view as well.

  14. Anti-globalization Actions – a Risk for Public Order and Safety

    OpenAIRE

    Cristian GISCA

    2010-01-01

    As a process, globalization has a long history. Some sustain that the current phase of globalization has nothing new, since its rise the capitalism was a transnational phenomenon. What is new, in the recent decades, is the amazing revolution of information and communication technology, which generated a qualitative and quantitative study of globalization process, especially on itseconomic dimension. On one hand, the process creates transnational networks, including people networks, and on the...

  15. 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.

  16. Bags Under Eyes

    Science.gov (United States)

    Bags under eyes Overview Bags under eyes — mild swelling or puffiness under the eyes — are common as you age. With aging, the tissues around your ... space below your eyes, adding to the swelling. Bags under eyes are usually a cosmetic concern and ...

  17. Affectivité et sentiment en économie politique : Cartas sobre los obstáculos que la naturaleza, la opinión y las leyes oponen a la felicidad pública du comte de Cabarrús (1795

    Directory of Open Access Journals (Sweden)

    Marc Marti

    2010-07-01

    Full Text Available Le travail qui suit est une étude sur l’émergence de l’économie politique en Espagne et de ses relations avec la rhétorique. Nous insistons en particulier sur le recours aux sentiments dans l’écriture d’une des œuvres de référence du premier libéralisme espagnole les Cartas sobre los obstáculos que la naturaleza, la opinión y las leyes oponen a la felicidad pública du comte de Cabarrús (1795.El siguiente trabajo estudia la emergencia de la economía política en España y sus relaciones con la retórica. Enfocamos en particular el uso de los sentimientos como procedimiento en la escritura de una obra que es una de las referencias mayores del primer liberalismo español, las Cartas sobre los obstáculos que la naturaleza, la opinión y las leyes oponen a la felicidad pública del conde de Cabarrús (1795.

  18. Solidarity under Attack

    DEFF Research Database (Denmark)

    Meret, Susi; Goffredo, Sergio

    2017-01-01

    https://www.opendemocracy.net/can-europe-make-it/susi-meret-sergio-goffredo/solidarity-under-attack......https://www.opendemocracy.net/can-europe-make-it/susi-meret-sergio-goffredo/solidarity-under-attack...

  19. PET's indsats under lup

    DEFF Research Database (Denmark)

    Hansen, Peer Henrik

    2006-01-01

    En undersøgelseskommission nedsat i 1999. Fem medlemmer skal undersøge PET's efterretningsvirksomhed i forhold til politiske partier, faglige konflikter og politisk ideologiske bevægelser i Danmark under den kolde krig. Kommissionens rapport forventes færdig næste år. Udgivelsesdato: 2. juli 2006...

  20. Flexicurity under afvikling?

    DEFF Research Database (Denmark)

    Schmidt, Johannes Dragsbæk; Crumlin, Jens Voldby

    2009-01-01

    Flexicurity-strategien er under angreb fra højrefløjen - mens Socialdemokrater og fagbevægelse er lammet Udgivelsesdato: 10 marts......Flexicurity-strategien er under angreb fra højrefløjen - mens Socialdemokrater og fagbevægelse er lammet Udgivelsesdato: 10 marts...

  1. Creativity under the Gun.

    Science.gov (United States)

    Amabile, Teresa M.; Hadley, Constance N.; Kramer, Steven J.

    2002-01-01

    Although many employers think that people are most creative when under time pressure, research indicates that the opposite is true. Data from 177 employees' diaries showed that creative thinking under extreme time pressure is unlikely when people feel on a treadmill or on autopilot; more likely when they feel they are on an expedition or a…

  2. Undersøgelse

    DEFF Research Database (Denmark)

    Hansen, Ernst Albin

    2010-01-01

    Cykelryttere får for lidt energidrik - og det koster dyrt på de lange distancer. Opsigtsvækkende resultater fra en ny undersøgelse afslører at væske- og energiindtaget under langvarig cykling har stor betydning for præstationen....

  3. Survival pathways under stress

    Indian Academy of Sciences (India)

    First page Back Continue Last page Graphics. Survival pathways under stress. Bacteria survive by changing gene expression. pattern. Three important pathways will be discussed: Stringent response. Quorum sensing. Proteins performing function to control oxidative damage.

  4. Equity valuation : Under Armour

    OpenAIRE

    Vicente, António Rafael Mendes

    2016-01-01

    The present dissertation aims to value Under Armour, an American sportswear company. Since Valuation is not an exact science, during the literature review will be presented several valuation methods. Most of the authors mention DCF Valuation as one of the best but it seems impossible for them to reach a consensus about which one is in fact the best. In order to get Under Armour’s target price, a DCF valuation will be made and accompanied by a Relative Valuation that, when it is properly us...

  5. Danmark under overfladen

    DEFF Research Database (Denmark)

    Hjorth, M.; Danø, R.

    "Danmark under overfladen" er et nyt undervisningstilbud til de danske skoler. På Internettet, www.danmarkunderoverfladen.dk kan man downloade grundbogen og fire andre temahæfter, samt se film og løse opgaver. "Danmark under overfladen" henvender sig til alle som er interesseret i havbiologi, men...... som undervisningsmateriale retter bogen sig særligt til de ældste klasser i folkeskolen og til det naturfaglige grundforløb i gymnasiet. Denne bog starter med at introducere den naturvidenskabelige arbejdsmetode i kapitel 1. Det er en tankegang som man må gå ind på,...

  6. Solidification under microgravity

    Indian Academy of Sciences (India)

    The paper outlines the broad areas where studies are being conducted under microgravity conditions worldwide viz., biotechnology, combustion science, materials science and fluid physics. The paper presents in particular a review on the various areas of research being pursued in materials science. These include studies ...

  7. Plants under dual attack

    NARCIS (Netherlands)

    Ponzio, C.A.M.

    2016-01-01

    Though immobile, plants are members of complex environments, and are under constant threat from a wide range of attackers, which includes organisms such as insect herbivores or plant pathogens. Plants have developed sophisticated defenses against these attackers, and include chemical responses such

  8. Care profession under change

    DEFF Research Database (Denmark)

    Rask Eriksen, Tine; Engel, Lisbeth Vinberg; Vedsegaard, Helle

    Backgound and aims: Sygeplejerskemanglen i Danmark er stor. Udfordringerne består i disse år i at rekruttere og fastholde sygeplejestuderende i studiet. Hensigten med projektet er dels at undersøge hvilke livshistoriske omsorgsforudsætninger, de studerende møder med i uddannelsen og dels at beskr...

  9. Network planning under uncertainties

    Science.gov (United States)

    Ho, Kwok Shing; Cheung, Kwok Wai

    2008-11-01

    One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a

  10. Creativity under the gun.

    Science.gov (United States)

    Amabile, Teresa M; Hadley, Constance N; Kramer, Steven J

    2002-08-01

    If you're like most managers, you've worked with people who swear they do their most creative work under tight deadlines. You may use pressure as a management technique, believing it will spur people on to great leaps of insight. You may even manage yourself this way. If so, are you right? Not necessarily, these researchers say. There are instances where ingenuity flourishes under extreme time pressure--for instance, a NASA team within hours comes up with a primitive but effective fix for the failing air filtration system aboard Apollo 13. But when creativity is under the gun, it usually ends up getting killed, the authors say. They recently took a close look at how people experience time pressure, collecting and analyzing more than 9,000 daily diary entries from individuals who were working on projects that required high levels of creativity and measuring their ability to innovate under varying levels of time pressure. The authors describe common characteristics of time pressure and outline four working environments under which creativity may or may not flourish. High-pressure days that still yield creativity are full of focus and meaningful urgency--people feel like they are on a mission. High-pressure days that yield no creativity lack such focus--people feel like they are on a treadmill, forced to switch gears often. On low-pressure days that yield creativity, people feel like they are on an expedition--exploring ideas rather than just identifying problems. And on low-pressure days that yield no creative thinking, people work on autopilot--doing their jobs without engaging too deeply. Managers should avoid extreme time pressure when possible; after all, complex cognitive processing takes time. For when they can't, the authors suggest ways to mollify its effects.

  11. [Cultural Identity, social health, and the Social State Under the rule of law. The case of "The Quimbaya Treasure". Quindío, Colombia].

    Science.gov (United States)

    Robledo-Martínez, Felipe A

    2015-07-01

    We approach the concept of "cultural identity" as a cohesive element within a group in the context of history and territory. We posit the relationship between this cultural identity with symbols of affiliation and origin, such as archeological heritage; in this case "The Quimbaya Treasure". We present "social health" as the capacity of a community, immersed in a culture and a territory, to relate healthily and cherish sentiments of support and trust. Rudiments of identity such as ancestral legacies allow for the creation of feelings of "sociocultural belonging" and self-determination of peoples that take paret in the health of a society. The autonomy of peoples and the recognition of their diversity appear in the notion of Nation State and Social State Under the Rule of Law. In this document, it is argued that, though the construction of this state was a political task, the edification of the nation was not. This edification was the result of earlier cultural labor. Nevertheless, historical rights are reflected in established constitutions. The Quimbaya Treasure was donated to Spain as part of Colombia's participation in ceremonies commemorating the 400th anniversary of the "Discovery of the Americas". This essay documents the legislative acts that prove the inconstitutionality of that donation and, as a result, the treasure's possible repatriation. It places emphasis on the importance of the repatriation given the value it possesses as an agent of cultural identity for Colombians in general and the residents of Quindío in particular.

  12. City under the Ice

    DEFF Research Database (Denmark)

    Nielsen, Kristian Hvidtfelt

    conflict that gave impetus to the camp’s construction. Presented to the public as a scientific station and a technologically-advanced, under-ice extension of the American way of life, while situated in the titanic struggle between West and East, Camp Century took on a number of closed-world meanings...... military conflicts are taking place. Studying the wealth of public representations of Camp Century, established 1959-60 by the US Army 128 miles east of the Thule Air Base and often referred to as the “City under the Ice”, we find a sharp contrast between the domesticated interior and the superpower......: The public image of Camp Century was one of technological comfort and military-scientific control. Amidst the raging Cold War and up against the harsh environment, the construction of the camp would prove to the public that the combined forces of the US military-technology-science complex would prevail...

  13. Child abuse: underlying mechanisms

    OpenAIRE

    Martínez, Gladys S.

    2009-01-01

    Exposure to traumatic stress during childhood, in the form of abuse or neglect, is related to an increased vulnerability resulting in the development of several pathologies, this relation has been confi rmed by epidemiological studies; however, the neural mechanisms underlying such abnormalities are still unknown. Most of the research done has focused on the effects in the infant, and only recently it has begun to focus on the neurobiological changes in the abusive parents. In this article, I...

  14. Poland under "Solidarity" Rule

    OpenAIRE

    Stanislaw Wellisz

    1991-01-01

    The coalition cabinet in which Solidarity played a leading role, but which also included Communists and their allies, won Parliamentary approval on September 12, 1989. This coalition inherited from the Communists an economy in deep crisis: inflation was raging, shortages of virtually all goods were rampant, and the black market was all-pervasive. The new government pledged to restore the market economy. This paper discusses the economy under Solidarity rule, focusing on stabilization and the ...

  15. R gas under diaphragm

    OpenAIRE

    Ramachar Sreevathsa, Maddibande; Melanta, Khyati

    2016-01-01

    Introduction: The most common cause of gas under diaphragm is hollow viscous perforation. In 10% of cases it can be due to rare causes, both abdominal and extra-abdominal, one of them being intra abdominal infection by gas forming organisms. Presentation of the case: A 51 year old male patient, a poorly controlled diabetic, presented with a second episode of severe pain abdomen and abdominal distention, with lower abdominal tenderness. Plain Xray of the abdomen in erect posture showed gas ...

  16. [Man and his fellow-creatures under ethical aspects].

    Science.gov (United States)

    Teutsch, Gotthard M

    2005-01-01

    It is for reasons of age I will have to terminate my work at the Literary Review in the form developed since 1995. The report is being reduced to a concentration of ethically relevant reviews as exemplified in the fourth-quarter issue of ALTEX. This is to ascertain that essential developments in this field will not be overlooked. Insofar, the Literary Review will be continued under the heading "New literature concerning topics of animal ethics". The more central topics of animal ethics are being "used up" the more new questions are being formulated. Thus it was that during the last few years the plant-world, long neglected, was rediscovered and received attention through the publication of important works. Another recent discovery concerns itself with "cognitive ethology" which developed out of the critique of behaviourism and which is dealt with in a separate chapter in this issue. But there is also a "classic" of ethics who has been reviewed and interpreted anew repeatedly. In her book "Albert Schweitzer, a prophet of medical ethics", Heike Baranzke describes Schweitzer's ethics as not sentimental or nostalgic but rather as a radically modern stance, committed to the enlightenment. Manuel Schneider, also, conveys a comprehensive view of Albert Schweitzer's ethics in "Life in the middle of life - the relevance of the ethics of Albert Schweitzer", a book edited by Altner, Frambach, Gottwald and himself in 2005. For this, in particular, he derives a possibility of a physiocentric ethics. By contrast, Beate Weinzierl approaches Schweitzer on a complete personal and human level in "Yearning for nature - access to inner and outer nature with Albert Schweitzer". Wolfgang Senz is undertaking a critical appreciation of Albert Schweitzer's concept of "life" and this, foremost, in the light of Schweitzer's rejection of the Cartesian "I am". In the end, Jean Claude Wolf cannot manage without citing Schweitzer either, referring to him in his not accepting the (western) world

  17. Evaporation under vacuum condition

    International Nuclear Information System (INIS)

    Mizuta, Satoshi; Shibata, Yuki; Yuki, Kazuhisa; Hashizume, Hidetoshi; Toda, Saburo; Takase, Kazuyuki; Akimoto, Hajime

    2000-01-01

    In nuclear fusion reactor design, an event of water coolant ingress into its vacuum vessel is now being considered as one of the most probable accidents. In this report, the evaporation under vacuum condition is evaluated by using the evaporation model we have developed. The results show that shock-wave by the evaporation occurs whose behavior strongly depends on the initial conditions of vacuum. And in the case of lower initial pressure and temperature, the surface temp finally becomes higher than other conditions. (author)

  18. Optimizing production under uncertainty

    DEFF Research Database (Denmark)

    Rasmussen, Svend

    This Working Paper derives criteria for optimal production under uncertainty based on the state-contingent approach (Chambers and Quiggin, 2000), and discusses po-tential problems involved in applying the state-contingent approach in a normative context. The analytical approach uses the concept...... of state-contingent production functions and a definition of inputs including both sort of input, activity and alloca-tion technology. It also analyses production decisions where production is combined with trading in state-contingent claims such as insurance contracts. The final part discusses...

  19. Balancing Machine Work, Comfort Work, and Sentimental Work

    DEFF Research Database (Denmark)

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

    2011-01-01

    To improve prehospital care ambulances carry increasingly sophisticated equipment aimed at initiating patient care already at the scene of injury. The competent use of this equipment is central to prehospital care but it also competes for increasing amounts of the ambulance crew’s time and attent......To improve prehospital care ambulances carry increasingly sophisticated equipment aimed at initiating patient care already at the scene of injury. The competent use of this equipment is central to prehospital care but it also competes for increasing amounts of the ambulance crew’s time...... 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...

  20. Facebook and Twitter vaccine sentiment in response to measles outbreaks.

    Science.gov (United States)

    Deiner, Michael S; Fathy, Cherie; Kim, Jessica; Niemeyer, Katherine; Ramirez, David; Ackley, Sarah F; Liu, Fengchen; Lietman, Thomas M; Porco, Travis C

    2017-11-01

    Social media posts regarding measles vaccination were classified as pro-vaccination, expressing vaccine hesitancy, uncertain, or irrelevant. Spearman correlations with Centers for Disease Control and Prevention-reported measles cases and differenced smoothed cumulative case counts over this period were reported (using time series bootstrap confidence intervals). A total of 58,078 Facebook posts and 82,993 tweets were identified from 4 January 2009 to 27 August 2016. Pro-vaccination posts were correlated with the US weekly reported cases (Facebook: Spearman correlation 0.22 (95% confidence interval: 0.09 to 0.34), Twitter: 0.21 (95% confidence interval: 0.06 to 0.34)). Vaccine-hesitant posts, however, were uncorrelated with measles cases in the United States (Facebook: 0.01 (95% confidence interval: -0.13 to 0.14), Twitter: 0.0011 (95% confidence interval: -0.12 to 0.12)). These findings may result from more consistent social media engagement by individuals expressing vaccine hesitancy, contrasted with media- or event-driven episodic interest on the part of individuals favoring current policy.

  1. Multi-Language Sentiment Analysis for Hotel Reviews

    Directory of Open Access Journals (Sweden)

    Sodanil Maleerat

    2016-01-01

    Full Text Available Touristes and traveler use avariety of information sources (e.g. travelportals, blogs, or social networking sites like twitter to help them decide for a hotel room. These sources all contain highly subjective text that expresses the opinions of many. We took a preliminary view on user generated hotel reviews from two travel portals in English and Thai. We developed a taxonomy of features and specifically investigated how accurately they can be predicted with three classification methods. The results indicate that support vector machines perform best for this specific domain.

  2. [Ritualistic female genital mutilation. The sentiment of the women].

    Science.gov (United States)

    Allag, F; Abboud, P; Mansour, G; Zanardi, M; Quéreux, C

    2001-11-01

    Female genital mutilation (FGM) is considered as the most dangerous custom still ritually practiced and 2 million girls undergo the ordeal each year. This practice is anchored and fixed firmly in numerous African people's culture and Western countries are confronted to it through African immigrants. In order to understand the justifications and the consequences of FGM we interviewed 14 genitally mutilated African women living in France. Unfortunately and despite the conscious knowledge of consequences and absurd side of such practice, yet it seems to be perpetuated over the descendants. Educational approach is the best solution to fight female genital mutilation fixed firmly in numerous African people's culture.

  3. Visualizing Host-Nation Sentiment at the Tactical Edge

    Science.gov (United States)

    2014-06-01

    HUMINT) and open source intelligence ( OSINT ) become prioritized above more traditional intelligence based on signals (SIGINT) and electronic sources...reliance on HUMINT and OSINT . Soldiers as peacekeepers must manage multiple information assets and resources, often relying on local and international

  4. Fuzzy-Set Based Sentiment Analysis of Big Social Data

    DEFF Research Database (Denmark)

    Mukkamala, Raghava Rao; Hussain, Abid; Vatrapu, Ravi

    2014-01-01

    Computational approaches to social media analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. There are no other unified modelling approaches to social data that integrate...... the conceptual, formal, software, analytical and empirical realms. In this paper, we first present and discuss a theory and conceptual model of social data. Second, we outline a formal model based on fuzzy set theory and describe the operational semantics of the formal model with a real-world social data example...... from Facebook. Third, we briefly present and discuss the Social Data Analytics Tool (SODATO) that realizes the conceptual model in software and provisions social data analysis based on the conceptual and formal models. Fourth, we use SODATO to fetch social data from the facebook wall of a global brand...

  5. A Dynamic Economic Model with Discrete Time and Consumer Sentiment

    Directory of Open Access Journals (Sweden)

    L. I. Dobrescu

    2009-01-01

    is replaced by a (quasi periodic motion. We associate the difference stochastic equation to the model by randomizing the control parameter d and by adding one stochastic control. Numerical simulations are made for the deterministic and stochastic models, for different values of the control parameter d.

  6. Chorégraphie sentimentale. Coreografía sentimental

    Directory of Open Access Journals (Sweden)

    Claude Murcia

    2012-04-01

    Full Text Available Sagitario (2001, film à la fois enjoué et mélancolique, présente une structure «mosaïque» qui substitue à la hiérarchisation des événements selon une logique causale la restitution d’un «état du monde». L’arbitraire de la contiguïté spatiale se joint à l’ubiquité énonciative pour construire un monde dominé par la discontinuité et l’inconstance. A l’éclatement structurel et à la dispersion du récit correspond la vision d’un sujet changeant et multiple qui semble mettre en échec tout principe de continuité malgré le recours –qu’on peut penser plaisamment générique– au «happy ending».Sagitario (2001 de Vicente Molina, película a la vez alegre y melan-cólica, presenta una estructura «mosaica» que frente a la jerar-quización de los hechos según una lógica causal, se sustituye por un «estado del mundo». La arbitra-riedad de la contigüidad espacial se une a la ubicuidad enunciativa para construir un mundo dominado por la discontinuidad y la inconstancia. A la ruptura estructural y a la dispersión del relato corresponde la visión de un sujeto cambiante y múltiple que parece derrotar todo principio de continuidad a pesar del recurso –que puede uno suponer lúdicamente genérico– al «happy end».

  7. Mathematically Gifted Adolescent Females' Mixed Sentiment toward Gender Stereotypes

    Science.gov (United States)

    Kao, Chen-yao

    2015-01-01

    There has been a paucity of research on gifted individuals' perceptions of gender stereotypes. The purpose of this study was to explore mathematically gifted adolescent females' perceptions of gender stereotypes through a research design of the qualitative multiple case study involving the constant comparison and the Three C's analysis scheme.…

  8. Sentiment analysis of feature ranking methods for classification accuracy

    Science.gov (United States)

    Joseph, Shashank; Mugauri, Calvin; Sumathy, S.

    2017-11-01

    Text pre-processing and feature selection are important and critical steps in text mining. Text pre-processing of large volumes of datasets is a difficult task as unstructured raw data is converted into structured format. Traditional methods of processing and weighing took much time and were less accurate. To overcome this challenge, feature ranking techniques have been devised. A feature set from text preprocessing is fed as input for feature selection. Feature selection helps improve text classification accuracy. Of the three feature selection categories available, the filter category will be the focus. Five feature ranking methods namely: document frequency, standard deviation information gain, CHI-SQUARE, and weighted-log likelihood –ratio is analyzed.

  9. Sentiment Analysis: A Perspective on its Past, Present and Future

    OpenAIRE

    Teeja Mary Sebastian; Akshi Kumar

    2012-01-01

    Abstract—The proliferation of Web-enabled devices, including desktops, laptops, tablets, and mobile phones, enables people to communicate, participate and collaborate with each other in various Web communities, viz., forums, social networks, blogs. Simultaneously, the enormous amount of heterogeneous data that is generated by the users of these communities, offers an unprecedented opportunity to create and employ theories & technologies that search and retrieve relevant data from the huge qua...

  10. Context-Sensitive Sentiment Classification of Short Colloquial Text

    NARCIS (Netherlands)

    Blenn, N.; Charalampidou, K.; Doerr, C.

    The wide-spread popularity of online social networks and the resulting availability of data to researchers has enabled the investigation of new research questions, such as the analysis of information diffusion and how individuals are influencing opinion formation in groups. Many of these new

  11. Sentiment Analysis of Suicide Notes: A Shared Task.

    Science.gov (United States)

    Pestian, John P; Matykiewicz, Pawel; Linn-Gust, Michelle; South, Brett; Uzuner, Ozlem; Wiebe, Jan; Cohen, K Bretonnel; Hurdle, John; Brew, Christopher

    2012-01-30

    This paper reports on a shared task involving the assignment of emotions to suicide notes. Two features distinguished this task from previous shared tasks in the biomedical domain. One is that it resulted in the corpus of fully anonymized clinical text and annotated suicide notes. This resource is permanently available and will (we hope) facilitate future research. The other key feature of the task is that it required categorization with respect to a large set of labels. The number of participants was larger than in any previous biomedical challenge task. We describe the data production process and the evaluation measures, and give a preliminary analysis of the results. Many systems performed at levels approaching the inter-coder agreement, suggesting that human-like performance on this task is within the reach of currently available technologies.

  12. Fuzzy-Set Based Sentiment Analysis of Big Social Data

    DEFF Research Database (Denmark)

    Mukkamala, Raghava Rao; Hussain, Abid; Vatrapu, Ravi

    Computational approaches to social media analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. There are no other unified modelling approaches to social data that integrate...... and actors on the facebook page. Sixth and last, we discuss the analytical method and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology....

  13. Intercrops under coconut plantations

    International Nuclear Information System (INIS)

    Mahmud, Z.

    1998-01-01

    The successes of growing intercrops under coconut plantations are controlled by environmental factors which are influenced by the coconut growth and characters, interception of solar radiation, as well as the coconut space and system of planting. Assuming that soil fertility be able to be manipulated by certain treatments, then climatic factors become priority to be considered for selection of intercrops. Coconut palms grow well on areas of 500 m asl., 27-32 deg. C temperature, and 1,500-3,000 mm in annual rainfall with even distribution throughout the year. Each kind (tall, dwarf, hybrid) of coconut performs specific growth characters, mainly on its root system and canopy coverage, as well as general conditions due to its growth phase (young, productive, senile). Above such conditions greatly influence the kind of crops suitable for development under coconut trees. However space and system of coconut planting give various conditions of interception solar radiation to ground surface, which means by manipulating both space and system, environmental requirement is able to be achieved accordingly [in

  14. Skolegang under anbringelse

    DEFF Research Database (Denmark)

    Perthou, Anette; Dam Mortensøn, Marie; Andersen, Dines

    Børn og unge, der er anbragt uden for hjemmet, klarer sig ofte dårligt i skolen. Det er især på døgninstitutioner og socialpædagogiske opholdssteder, at børnene halter bagefter, og der er derfor behov for et øget fokus på skolegangen på disse institutioner. SFI har via kvalitative interview med...... ledere, pædagoger og lærere på otte institutioner samt tilknyttede medarbejdere fra den kommunale PPR undersøgt, hvilke forhold der har betydning for anbragte børns skolegang. Rapporten fokuserer dels på samarbejdet mellem de professionelle faggrupper, der er involveret i de anbragte børns og unges...

  15. Attractors under discretisation

    CERN Document Server

    Han, Xiaoying

    2017-01-01

    This work focuses on the preservation of attractors and saddle points of ordinary differential equations under discretisation. In the 1980s, key results for autonomous ordinary differential equations were obtained – by Beyn for saddle points and by Kloeden & Lorenz for attractors. One-step numerical schemes with a constant step size were considered, so the resulting discrete time dynamical system was also autonomous. One of the aims of this book is to present new findings on the discretisation of dissipative nonautonomous dynamical systems that have been obtained in recent years, and in particular to examine the properties of nonautonomous omega limit sets and their approximations by numerical schemes – results that are also of importance for autonomous systems approximated by a numerical scheme with variable time steps, thus by a discrete time nonautonomous dynamical system.

  16. Chilean economy under Pinochet

    Directory of Open Access Journals (Sweden)

    Libor Žídek

    2005-01-01

    Full Text Available Period of Pinochet rule in Chile is still in the centre of interest of many experts. This article concentrates (mostly on the economic side of the military rule. Pinochet took responsibility for the country in situation near to economic collapse caused by policy of the previous – Allendeęs government. The new government after the coup dęétat in 1973 had to stabilize economy. Soldiers at the same time start to implement economic reforms that improved the long run ability of the economy to grow. The economic uplift was interrupted by debt crisis at the beginning of 1980s. Pinochetęs government was able to deal with these obstacles and at the end passed the economy to the democratic government (at the end of 1980s in good shape. The following positive development in the 1990s is thus based on the foundations built under the military rule.

  17. A life under pressure

    DEFF Research Database (Denmark)

    Jacobsen, Jens Christian Brings; von Holstein-Rathlou, Niels-Henrik

    2012-01-01

    Microvessels live 'a life under pressure' in several ways. In a literal sense, vessels of the microcirculation are exposed to high levels of stress caused primarily by the intravascular pressure head. In a figurative sense, the individual vessel and the microvascular network as a whole must...... continuously strive to meet the changing demands of the surrounding tissue. The 'principle of optimal operation' as formulated by Y. C. Fung states that living tissues adapts structurally through remodelling and growth until a level of tensile and compressive stresses is reached at which tissue performance...... stress component has a huge impact on the state of the vascular wall. It is involved as a unifying factor on vastly different timescales in processes as diverse as acute regulation of vessel diameter, structural vessel remodelling and growth or atrophy of the vascular wall. The aim of this Mini...

  18. Calibration Under Uncertainty.

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, Laura Painton; Trucano, Timothy Guy

    2005-03-01

    This report is a white paper summarizing the literature and different approaches to the problem of calibrating computer model parameters in the face of model uncertainty. Model calibration is often formulated as finding the parameters that minimize the squared difference between the model-computed data (the predicted data) and the actual experimental data. This approach does not allow for explicit treatment of uncertainty or error in the model itself: the model is considered the %22true%22 deterministic representation of reality. While this approach does have utility, it is far from an accurate mathematical treatment of the true model calibration problem in which both the computed data and experimental data have error bars. This year, we examined methods to perform calibration accounting for the error in both the computer model and the data, as well as improving our understanding of its meaning for model predictability. We call this approach Calibration under Uncertainty (CUU). This talk presents our current thinking on CUU. We outline some current approaches in the literature, and discuss the Bayesian approach to CUU in detail.

  19. Politics Under Electronic Simultaneity

    Directory of Open Access Journals (Sweden)

    Valery P. Terin

    2014-01-01

    Full Text Available In contradistinction to the book and the other typographic products, the electronic media operates on a 24-hour-a-day basis evoking simultaneity as the guiding mode of perception and thinking for all those under its influence. The discovery of this fact manifested itself in the formation and development of the managerial technologies operating by means of the electronic information environment and following the principle of simultaneity in the first place. Thus, at the end of the 1960s already the election campaigns in the U.S.A. began to operate on the basis of the final cause as the guiding principle of the country's mass consciousness motivating to carry out each particular event as if already rejoicing at the victory. With this in mind, there emerged a problem of applying this approach with its enormous managerial potential elsewhere. To add, simultaneity as a norm of perception and thinking turned out to be increasingly important with the advent of the electrical telegraph and the press relying on its short disconnected messages instantaneously arriving from all parts of the world. All the other media, which emerged in the wake of this development, has served to fortify this mode of thought as governing in the electronic information environment. The potential of the electronically operating global managerial technologies is quickly growing. The article also deals with the information overload and pattern recognition problem understood in managerial terms as well as mythologization and demythologization processes as they are necessitated by the electronic media coverage worldwide.

  20. Undersøgelsesdesign

    DEFF Research Database (Denmark)

    Hansbøl, Mikala

    2014-01-01

    Delrapport fra LUG-projektet, delprojekt A - Uddannelsesinstitutionelle Grænser. I 2014 udvikler og forsker UCSJ og RUC i en gratis og fleksibel måde at udbyde uddannelse på, inspireret af flere universiteter i USA – via MOOCs (Multiple Open Online Courses). MOOC-projektet er en del af et større...... innovationsprojekt “Læring Uden Grænser” - støttet af den Den Europæiske Fond for Regionaludvikling. Projektet undersøger hvordan digitale teknologier og nye koblinger i form af netværk- og institutionssamarbejde kan mindske grænser for læring i Region Sjælland. Den næste år udvikles og udbydes en række MOOCs, der...... skal generere og formidle ny viden om, hvordan MOOCs kan udvikles på måder, så også regionale hensyn tages. Projektet arbejder designbaseret og der vil derfor gennem input fra brugere, partnere, arrangerede workshops, og lignende foregå en løbende redesignproces. Projektet vil munde ud i en række...

  1. WHn under pressure

    International Nuclear Information System (INIS)

    Zaleski-Ejgierd, Patryk; Ashcroft, N W; Labet, Vanessa; Hoffmann, Roald; Strobel, Timothy A

    2012-01-01

    An initial observation of the formation of WH under pressure from W gaskets surrounding hydrogen in diamond anvil cells led to a theoretical study of tungsten hydride phases. At P = 1 atm no stoichiometry is found to be stable with respect to separation into the elements, but as the pressure is raised WH n (n = 1-6, 8) stoichiometries are metastable or stable. WH and WH 4 are calculated to be stable at P > 15 GPa, WH 2 becomes stable at P > 100 GPa and WH 6 at P > 150 GPa. In agreement with experiment, the structure computed for WH is anti-NiAs. WH 2 shares with WH a hexagonal arrangement of tungsten atoms, with hydrogen atoms occupying octahedral and tetrahedral holes. For WH 4 the W atoms are in a distorted fcc arrangement. As the number of hydrogens rises, the coordination of W by H increases correspondingly, leading to a twelve-coordinated W in WH 6 . In WH 8 H 2 units also develop. All of the hydrides considered should be metallic at high pressure, though the Fermi levels of WH 4 and WH 6 lie in a deep pseudogap. Prodded by these theoretical studies, experiments were then undertaken to seek phases other than WH, exploring a variety of experimental conditions that would favor further reaction. Though a better preparation and characterization of WH resulted, no higher hydrides have as yet been found. (paper)

  2. Memory dynamics under stress.

    Science.gov (United States)

    Quaedflieg, Conny W E M; Schwabe, Lars

    2018-03-01

    Stressful events have a major impact on memory. They modulate memory formation in a time-dependent manner, closely linked to the temporal profile of action of major stress mediators, in particular catecholamines and glucocorticoids. Shortly after stressor onset, rapidly acting catecholamines and fast, non-genomic glucocorticoid actions direct cognitive resources to the processing and consolidation of the ongoing threat. In parallel, control of memory is biased towards rather rigid systems, promoting habitual forms of memory allowing efficient processing under stress, at the expense of "cognitive" systems supporting memory flexibility and specificity. In this review, we discuss the implications of this shift in the balance of multiple memory systems for the dynamics of the memory trace. Specifically, stress appears to hinder the incorporation of contextual details into the memory trace, to impede the integration of new information into existing knowledge structures, to impair the flexible generalisation across past experiences, and to hamper the modification of memories in light of new information. Delayed, genomic glucocorticoid actions might reverse the control of memory, thus restoring homeostasis and "cognitive" control of memory again.

  3. Strategy under uncertainty.

    Science.gov (United States)

    Courtney, H; Kirkland, J; Viguerie, P

    1997-01-01

    At the heart of the traditional approach to strategy lies the assumption that by applying a set of powerful analytic tools, executives can predict the future of any business accurately enough to allow them to choose a clear strategic direction. But what happens when the environment is so uncertain that no amount of analysis will allow us to predict the future? What makes for a good strategy in highly uncertain business environments? The authors, consultants at McKinsey & Company, argue that uncertainty requires a new way of thinking about strategy. All too often, they say, executives take a binary view: either they underestimate uncertainty to come up with the forecasts required by their companies' planning or capital-budging processes, or they overestimate it, abandon all analysis, and go with their gut instinct. The authors outline a new approach that begins by making a crucial distinction among four discrete levels of uncertainty that any company might face. They then explain how a set of generic strategies--shaping the market, adapting to it, or reserving the right to play at a later time--can be used in each of the four levels. And they illustrate how these strategies can be implemented through a combination of three basic types of actions: big bets, options, and no-regrets moves. The framework can help managers determine which analytic tools can inform decision making under uncertainty--and which cannot. At a broader level, it offers executives a discipline for thinking rigorously and systematically about uncertainty and its implications for strategy.

  4. Contextuality under weak assumptions

    International Nuclear Information System (INIS)

    Simmons, Andrew W; Rudolph, Terry; Wallman, Joel J; Pashayan, Hakop; Bartlett, Stephen D

    2017-01-01

    The presence of contextuality in quantum theory was first highlighted by Bell, Kochen and Specker, who discovered that for quantum systems of three or more dimensions, measurements could not be viewed as deterministically revealing pre-existing properties of the system. More precisely, no model can assign deterministic outcomes to the projectors of a quantum measurement in a way that depends only on the projector and not the context (the full set of projectors) in which it appeared, despite the fact that the Born rule probabilities associated with projectors are independent of the context. A more general, operational definition of contextuality introduced by Spekkens, which we will term ‘probabilistic contextuality’, drops the assumption of determinism and allows for operations other than measurements to be considered contextual. Even two-dimensional quantum mechanics can be shown to be contextual under this generalised notion. Probabilistic noncontextuality represents the postulate that elements of an operational theory that cannot be distinguished from each other based on the statistics of arbitrarily many repeated experiments (they give rise to the same operational probabilities) are ontologically identical. In this paper, we introduce a framework that enables us to distinguish between different noncontextuality assumptions in terms of the relationships between the ontological representations of objects in the theory given a certain relation between their operational representations. This framework can be used to motivate and define a ‘possibilistic’ analogue, encapsulating the idea that elements of an operational theory that cannot be unambiguously distinguished operationally can also not be unambiguously distinguished ontologically. We then prove that possibilistic noncontextuality is equivalent to an alternative notion of noncontextuality proposed by Hardy. Finally, we demonstrate that these weaker noncontextuality assumptions are sufficient to prove

  5. RESTRUCTURING COMPANIES UNDER CRISIS

    Directory of Open Access Journals (Sweden)

    Hezi Aviram SHAYB

    2016-12-01

    Full Text Available Nobody is planning to fail, but many companies are failing because of lack of planning. Real business experience showed during the years that crisis can be prevented, avoided or limited. If detected in time, the risks associated with the crisis can be mitigated and the effects can be diminished, with the condition that the actions required are done fast, in a sharp and accurate manner. When it comes, a crisis brings an intense level of pressure and under these conditions there is no time or room for mistakes. Delays, losing focus and lack of planning will bring a company one step away from failure. The right way to deal with crisis, if required measures are not done in time, is to minimize the losses and reposition in the best way possible. Analysing the success stories of some of the biggest and strongest companies in the world, led to an important conclusion: the majority of these companies were in the situation to face huge crises which threatened their ability to survive in certain moments, on their way to success. With the right planning and by setting a proper organisational structure, the negative aspects of the crisis can be turned into benefits and opportunities for the company. The most critical challenge for management is to assess the level of exposure to risk of the company and identify the key points to focus on in order to overcome the crisis and create value. In order to set up a strong plan in dealing with crisis, a business organisation needs reliable, efficient and effective tools and this is what this article is all about.

  6. 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.

  7. NGSS, disposability, and the ambivalence of science in/under neoliberalism

    Science.gov (United States)

    Weinstein, Matthew

    2017-12-01

    This paper explores the ambivalence of the Next Generation Science Standards (NGSS) and its Framework towards neoliberal governance. The paper examines the ways that the NGSS serves as a mechanism within neoliberal governance: in its production of disposable populations through testing and through the infusion of engineering throughout the NGSS to resolve social problems through technical fixes. However, the NGSS, like earlier standards, is reactionary to forces diminishing the power of institutional science (e.g., the AAAS) including neoliberal prioritizing market value over evidence. The NGSS explicitly takes on neoliberal junk science such as the anti-global-warming Heartland Institute.

  8. 'Agony aunt, hostage, intruder or friend?'. The multiple personas of the interviewer during fieldwork 'Agony aunt, hostage, intruder or friend?'. The multiple personas of the interviewer during fieldwork ¿Consultor sentimental, intruso, rehén o amigo? Los múltiples papeles del entrevistador durante el trabajo de campo

    Directory of Open Access Journals (Sweden)

    Valerie Caven

    2012-12-01

    researchers/interviewers in different interview situations. Practical implications: The research has practical value in highlighting the multiple facets of the relationship between interviewer and interviewee in qualitative research. It will be of value to both experienced and new researchers. Originality/value: The development of the typology represents the originality and value of the research. Previous research has focused more on telling the stories rather than the development of new theory relating to interviewing.Objeto: Este artículo analiza la manera en la que los entrevistados manipulan el papel del entrevistador durante la realización de entrevistas cualitativas de investigación, todo ello a cambio de que los entrevistados compartan sus experiencias, opiniones e información. Diseño/metodología/enfoque: De acuerdo con el paradigma de investigación cualitativo, se hicieron entrevistas semi estructuradas a 55 arquitectos de la región de East Midlands en el Reino Unido. Además de las entrevistas la entrevistadora tomó notas acerca de la situación de entrevista con el objeto de formar el diario de investigación. Aportaciones y resultados: Se presenta una tipología de 4 personajes de entrevistador: “consultor sentimental, rehén, intruso o amigo”. Limitaciones de la investigación/implicaciones: La tipología de entrevistadores surge del análisis del papel representado por un único entrevistador. Sin embargo, los resultados pueden aplicarse a otros investigadores/entrevistadores en distintas situaciones de entrevista. Implicaciones Prácticas: Este trabajo tiene valor práctico puesto que pone de relieve las múltiples facetas de la relación entrevistador-entrevistado en la investigación cualitativa. Puede resultar útil tanto para investigadores experimentados como noveles. Originalidad/valor añadido: La originalidad y el valor de la investigación residen en la identificación y el desarrollo de la tipología de personajes. Investigaciones previas

  9. Underlying Event Measurements at CMS

    CERN Document Server

    Gupta, Rajat

    2017-01-01

    Measurements of Underlying Event activity using proton-proton collision data collected by the CMS detector will be presented. To check the energy dependence of the underlying event activity, results are compared with previous measurements from different experiments at different centre-of-mass energies.

  10. Prevalence of Under Nutrition among Under Five Year Children in ...

    African Journals Online (AJOL)

    Nigeria. ... International Journal of Community Research ... The nutritional status of under-five children is a reflection of the health of children in the community and this forms the basis for the development of success–oriented interventional ...

  11. Frivillig og under eget ansvar

    DEFF Research Database (Denmark)

    Bang, Karin

    2002-01-01

    Ifølge Lou Andreas-Salomé drejer flere af Henrik Ibsens dramaer sig om problemet med at skabe balance mellem selvbefrielse og selvbegrænsning, og nøgleordene er: Frivillig og under eget ansvar....

  12. Refugee scientists under the spotlight

    Science.gov (United States)

    Extance, Andy

    2017-07-01

    Thousands of people are forced to flee war-torn regions every year, but the struggles of scientists who have to leave their homeland often goes under the radar. Andy Extance reports on initiatives to help

  13. Logistics systems optimization under competition

    DEFF Research Database (Denmark)

    Choi, Tsan Ming; Govindan, Kannan; Ma, Lijun

    2015-01-01

    Nowadays, optimization on logistics and supply chain systems is a crucial and critical issue in industrial and systems engineering. Important areas of logistics and supply chain systems include transportation control, inventory management, and facility location planning. Under a competitive market...

  14. Graphene cantilever under Casimir force

    Science.gov (United States)

    Derras-Chouk, Amel; Chudnovsky, Eugene M.; Garanin, Dmitry A.; Jaafar, Reem

    2018-05-01

    The stability of graphene cantilever under Casimir attraction to an underlying conductor is investigated. The dependence of the instability threshold on temperature and flexural rigidity is obtained. Analytical work is supplemented by numerical computation of the critical temperature above which the graphene cantilever irreversibly bends down and attaches to the conductor. The geometry of the attachment and exfoliation of the graphene sheet is discussed. It is argued that graphene cantilever can be an excellent tool for precision measurements of the Casimir force.

  15. Sustaining dry surfaces under water

    DEFF Research Database (Denmark)

    Jones, Paul R.; Hao, Xiuqing; Cruz-Chu, Eduardo R.

    2015-01-01

    not been investigated, and are critically important to maintain surfaces dry under water.In this work, we identify the critical roughness scale, below which it is possible to sustain the vapor phase of water and/or trapped gases in roughness valleys – thus keeping the immersed surface dry. Theoretical......Rough surfaces immersed under water remain practically dry if the liquid-solid contact is on roughness peaks, while the roughness valleys are filled with gas. Mechanisms that prevent water from invading the valleys are well studied. However, to remain practically dry under water, additional...... mechanisms need consideration. This is because trapped gas (e.g. air) in the roughness valleys can dissolve into the water pool, leading to invasion. Additionally, water vapor can also occupy the roughness valleys of immersed surfaces. If water vapor condenses, that too leads to invasion. These effects have...

  16. Equity valuation of Under Armour

    OpenAIRE

    Diogo, Rafael Martins Ribeiro

    2017-01-01

    A dissertação aqui apresentada tem como objetivo apresentar uma avaliação para a Under Armour, - empresa que desenvolve a sua atividade na indústria do equipamento desportivo. A Under Armour representa um exemplo de empreendedorismo, determinação e excelência, personalizada pelo seu fundador e atual diretor executivo. Kevin Plank criou a empresa em 1996, com apenas 23 anos, através do desenvolvimento de um protótipo de uma t-shirt desportiva. Entretanto, a empresa já experienciou uma OPA e...

  17. Residual Liquefaction under Standing Waves

    DEFF Research Database (Denmark)

    Kirca, V.S. Ozgur; Sumer, B. Mutlu; Fredsøe, Jørgen

    2012-01-01

    This paper summarizes the results of an experimental study which deals with the residual liquefaction of seabed under standing waves. It is shown that the seabed liquefaction under standing waves, although qualitatively similar, exhibits features different from that caused by progressive waves....... The experimental results show that the buildup of pore-water pressure and the resulting liquefaction first starts at the nodal section and spreads towards the antinodal section. The number of waves to cause liquefaction at the nodal section appears to be equal to that experienced in progressive waves for the same...

  18. Regulating renewable resources under uncertainty

    DEFF Research Database (Denmark)

    Hansen, Lars Gårn

    Renewable natural resources (like water, fish and wildlife stocks, forests and grazing lands) are critical for the livelihood of millions of people and understanding how they can be managed efficiently is an important economic problem. I show how regulator uncertainty about different economic......) that a pro-quota result under uncertainty about prices and marginal costs is unlikely, requiring that the resource growth function is highly concave locally around the optimum and, 3) that quotas are always preferred if uncertainly about underlying structural economic parameters dominates. These results...

  19. Export Taxes under Bertrand Duopoly

    OpenAIRE

    David Collie; Roger Clarke

    2006-01-01

    This article analyses export taxes in a Bertrand duopoly with product differentiation, where a home and a foreign firm both export to a third-country market. It is shown that the maximum-revenue export tax always exceeds the optimum-welfare export tax. In a Nash equilibrium in export taxes, the country with the low cost firm imposes the largest export tax. The results under Bertrand duopoly are compared with those under Cournot duopoly. It is shown that the absolute value of the export subsid...

  20. Tvangslånene. Om fiskale forhold i Slesvig under og efter Treårskrigen

    DEFF Research Database (Denmark)

    Clausen, Thomas

    2013-01-01

    the districts of the region. However, only the two first were actually collected as the final one was decided just a few months before the end of the war. The compulsory loans were a war tax, with the particular characteristic though, that in principle those citizens who contributed enjoyed status as creditors...... or after some persuasion, seeing it as a civil duty and/or a sensible investment. On a number of occasions though, especially in the northern districts where pro-Danish sentiments prevailed, local residents would only pay up after threats by central authorities to take possession by military execution...

  1. Investment under Uncertain Climate Policy

    DEFF Research Database (Denmark)

    Barradale, Merrill Jones

    2014-01-01

    This paper introduces the concept of payment probability as an important component of carbon risk (the financial risk associated with CO2 emissions under uncertain climate policy). In modeling power plant investment decisions, most existing literature uses the expected carbon price (e.g., the price...

  2. Underlying Mechanisms Affecting Institutionalisation of ...

    African Journals Online (AJOL)

    This paper discusses the underlying causal mechanisms that enabled or constrained institutionalisation of environmental education in 12 institutions in eight countries in southern Africa. The study was carried out in the context of the Southern Africa Development Community Regional Environmental Education Support ...

  3. Intumescent coatings under fast heating

    DEFF Research Database (Denmark)

    Nørgaard, Kristian Petersen; Dam-Johansen, Kim; Català, Pere

    2012-01-01

    Intumescent coatings are widely used to delay or minimise the destructive effects of fire. They are usually tested under conditions that simulate the relatively slow build-up of heat in a normal fire. Here, the effects of damage during a fire causing sudden heating of the coating were studied....

  4. Subsidized Capacity Investment under Uncertainty

    NARCIS (Netherlands)

    Wen, Xingang; Hagspiel, V.; Kort, Peter

    2017-01-01

    This paper studies how the subsidy support, e.g. price support and reimbursed investment cost support, affects the investment decision of a monopoly firm under uncertainty and analyzes the implications for social welfare. The analytical results show that the unconditional, i.e., subsidy support that

  5. Under pres for at tilgive

    DEFF Research Database (Denmark)

    Gade, Christian B.N.

    2013-01-01

    Efter afslutningen på apartheid i sydafrika etablerede landets nye parlament en sandheds- og forsoningskommission, hvor ofre for apartheid fik mulighed for at fortælle deres historier under offentlige høringer i kommissions komité for menneskerettighedskrænkelser. I løbet af kommissionens arbejde...

  6. Inclusive Education under Collectivistic Culture

    Science.gov (United States)

    Futaba, Yasuko

    2016-01-01

    This paper addresses how inclusive education under collective culture is possible. Inclusive education, which more-or-less involves changing the current schools, has been denied, doubted or distorted by both policy-makers and practitioners of general and special education in Japan. Main reason for the setback in inclusive education can be…

  7. Underlying Mechanisms Affecting Institutionalisation of ...

    African Journals Online (AJOL)

    doctoral study and draws on critical realism as the ontological lens. Data analysis was done by means of a retroductive mode of inference, as articulated by Danermark, Ekström, Jakosben and Karlsson (2002). The paper demonstrates that there are a number of underlying causal mechanisms, which may enable or.

  8. Molecular mechanisms underlying bacterial persisters

    DEFF Research Database (Denmark)

    Maisonneuve, Etienne; Gerdes, Kenn

    2014-01-01

    All bacteria form persisters, cells that are multidrug tolerant and therefore able to survive antibiotic treatment. Due to the low frequencies of persisters in growing bacterial cultures and the complex underlying molecular mechanisms, the phenomenon has been challenging to study. However, recent...

  9. Practice research under changing conditions

    DEFF Research Database (Denmark)

    Dreier, Ole

    particularly important in unraveling what is glossed over or reinterpreted beyond recognition. Doing so helps putting psychology back on its feet. But practice research was developed under other social, political and professional conditions and under other regimes of knowledge than we find today where...... research in critical psychology is based on a science of the subject – as opposed to the science of control dominating psychology. Of course, projects involve many subjects with diverse perspectives on the issues at hand. Descriptions of practices from subject positions previously considered negligible......The tradition of practice research emerged in critical psychology in Germany and Denmark about twenty-five years ago. It emphasizes the relevance of knowledge - above all knowledge for change - by researching exemplary scopes of possibilities for agents in particular kinds of situations. A key...

  10. Modelling microstructural evolution under irradiation

    International Nuclear Information System (INIS)

    Tikare, V.

    2015-01-01

    Microstructural evolution of materials under irradiation is characterised by some unique features that are not typically present in other application environments. While much understanding has been achieved by experimental studies, the ability to model this microstructural evolution for complex materials states and environmental conditions not only enhances understanding, it also enables prediction of materials behaviour under conditions that are difficult to duplicate experimentally. Furthermore, reliable models enable designing materials for improved engineering performance for their respective applications. Thus, development and application of mesoscale microstructural model are important for advancing nuclear materials technologies. In this chapter, the application of the Potts model to nuclear materials will be reviewed and demonstrated, as an example of microstructural evolution processes. (author)

  11. Nano controllers characterization under radiation

    International Nuclear Information System (INIS)

    Bezerra, F.; Barde, S.; Carayon, J.L.; Sarthou, M.

    1999-01-01

    4 commercial nano-controllers (PIC16LC84, PIC16C73A, PIC16C76 and ST62E25) from MICROCHIP and SGS-Thomson have been characterized under heavy-ions, protons and total dose. The preliminary results show that PIC16LC84 has to be banned from the selection because it can not sustain high cumulated dose (its Idd begins to shift at 6 krads) and that its E 2 PROM code memory is too sensitive to SEU (single event upset). The 3 PICs have been tested with heavy-ions, the results show that they are sensible to upsets and latch-up, nevertheless no latch-up has been observed under proton irradiation. The sensitivity to latch-up does not matter a lot because PICs consume very little and it is planned to implement them in a tolerant design. (A.C.)

  12. CONSOLIDATED FINANCIAL STATEMENTS UNDER IFRS

    OpenAIRE

    Tănase Alin-Eliodor; Calotă Traian-Ovidiu

    2013-01-01

    This article is focuses on accounting consolidation techniques and the preparation of consolidation worksheets for the components of financial statements (statement of comprehensive income, statement of changes in equity, and financial position). The presented group includes parent company, two subsidiaries (only one fully controlled by the parent company) and a jointly controlled entity. The financial statements are presented under the following standards IFRS 3 Business Combination, IAS 27 ...

  13. Chemical model reduction under uncertainty

    KAUST Repository

    Najm, Habib

    2016-01-05

    We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.

  14. Tort law under oligopolistic competition

    OpenAIRE

    Mondello, Gérard; Salies, Evens

    2016-01-01

    This article extends the unilateral accident standard model to allow for Cournot competition. Assuming risk-neutrality for the regulator and injurers, it analyzes three liability regimes: strict liability, negligence rule, and strict liability with administrative authorization or permits systems. Under competition the equivalence between negligence rule and strict liability no longer holds, and negligence insures a better level of social care. However, enforcing both a permit system and ...

  15. Analytical methods under emergency conditions

    International Nuclear Information System (INIS)

    Sedlet, J.

    1983-01-01

    This lecture discusses methods for the radiochemical determination of internal contamination of the body under emergency conditions, here defined as a situation in which results on internal radioactive contamination are needed quickly. The purpose of speed is to determine the necessity for medical treatment to increase the natural elimination rate. Analytical methods discussed include whole-body counting, organ counting, wound monitoring, and excreta analysis. 12 references

  16. Ultrasonic sludge pretreatment under pressure.

    Science.gov (United States)

    Le, Ngoc Tuan; Julcour-Lebigue, Carine; Delmas, Henri

    2013-09-01

    The objective of this work was to optimize the ultrasound (US) pretreatment of sludge. Three types of sewage sludge were examined: mixed, secondary and secondary after partial methanisation ("digested" sludge). Thereby, several main process parameters were varied separately or simultaneously: stirrer speed, total solid content of sludge (TS), thermal operating conditions (adiabatic vs. isothermal), ultrasonic power input (PUS), specific energy input (ES), and for the first time external pressure. This parametric study was mainly performed for the mixed sludge. Five different TS concentrations of sludge (12-36 g/L) were tested for different values of ES (7000-75,000 kJ/kgTS) and 28 g/L was found as the optimum value according to the solubilized chemical oxygen demand in the liquid phase (SCOD). PUS of 75-150 W was investigated under controlled temperature and the "high power input - short duration" procedure was the most effective at a given ES. The temperature increase in adiabatic US application significantly improved SCOD compared to isothermal conditions. With PUS of 150 W, the effect of external pressure was investigated in the range of 1-16 bar under isothermal and adiabatic conditions for two types of sludge: an optimum pressure of about 2 bar was found regardless of temperature conditions and ES values. Under isothermal conditions, the resulting improvement of sludge disintegration efficacy as compared to atmospheric pressure was by 22-67% and 26-37% for mixed and secondary sludge, respectively. Besides, mean particle diameter (D[4,3]) of the three sludge types decreased respectively from 408, 117, and 110 μm to about 94-97, 37-42, and 36-40 μm regardless of sonication conditions, and the size reduction process was much faster than COD extraction. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. 16 MW under the seas

    International Nuclear Information System (INIS)

    Mary, Olivier

    2014-01-01

    This article presents the Nemo project (Nemo stands for New Energy for Martinique and Overseas) and its precursor project, Ner 300, developed in cooperation between Akuo Energy and DCNS, and which is financed by the European Bank for Investment. These projects aim at exploiting sea thermal energy. Ner 300 will exploit the 20 degree difference between surface waters (25 C) and deep waters (5 C at 1.000 m under sea level). The article evokes works performed by DCNS to develop a prototype near the Reunion Island. The principle and operation are briefly described, and technological challenges are outlined

  18. Cellulose conversion under heterogeneous catalysis.

    Science.gov (United States)

    Dhepe, Paresh L; Fukuoka, Atsushi

    2008-01-01

    In view of current problems such as global warming, high oil prices, food crisis, stricter environmental laws, and other geopolitical scenarios surrounding the use of fossil feedstocks and edible resources, the efficient conversion of cellulose, a non-food biomass, into energy, fuels, and chemicals has received much attention. The application of heterogeneous catalysis could allow researchers to develop environmentally benign processes that lead to selective formation of value-added products from cellulose under relatively mild conditions. This Minireview gives insight into the importance of biomass utilization, the current status of cellulose conversion, and further transformation of the primary products obtained.

  19. SULFENTRAZONE PHYTOREMEDIATION UNDER FIELD CONDITIONS

    Directory of Open Access Journals (Sweden)

    ALESSANDRA FERREIRA BELO

    2016-01-01

    Full Text Available Phytoremediation is a technique that has been used with increasing frequency to decontaminate soils treated with herbicides that have long - term residual effects, such as sulfentrazone. The goal was to assess phytoremediation of the herbicide sulfentrazone under field conditions by the species Canavalia ensiformis and Crotalaria juncea . The treatments consisted of combinations of the plant species C. ensiformis and C. juncea plus a control treatment (with manual weeding and four doses of the herbicide sulfentrazone. The experimental design used herein was a split - plot randomized block design with four replicates per subplot. The treatments were kept in the field for 75 days. After this period, the experimental area was again furrowed and fertilized, considering the requirements for Pennisetum glaucum , a plant used as an indicator of the presence of sulfentrazone. Thirty - four days after sowing pearl millet, the fresh and dry shoot masses of the plants were assessed. At the end of the cycle, the plant height, stem diameter, internode length, number of leaves, number of panicles, and fresh and dry panicle masses were determined. Previous cultivation of phytoremediation species C. ensiformis and C. juncea promotes sulfentrazone remediation. C. ensiformis is the most efficient species for the decontamination of the herbicide sulfentrazone under field conditions.

  20. Haldane model under nonuniform strain

    Science.gov (United States)

    Ho, Yen-Hung; Castro, Eduardo V.; Cazalilla, Miguel A.

    2017-10-01

    We study the Haldane model under strain using a tight-binding approach, and compare the obtained results with the continuum-limit approximation. As in graphene, nonuniform strain leads to a time-reversal preserving pseudomagnetic field that induces (pseudo-)Landau levels. Unlike a real magnetic field, strain lifts the degeneracy of the zeroth pseudo-Landau levels at different valleys. Moreover, for the zigzag edge under uniaxial strain, strain removes the degeneracy within the pseudo-Landau levels by inducing a tilt in their energy dispersion. The latter arises from next-to-leading order corrections to the continuum-limit Hamiltonian, which are absent for a real magnetic field. We show that, for the lowest pseudo-Landau levels in the Haldane model, the dominant contribution to the tilt is different from graphene. In addition, although strain does not strongly modify the dispersion of the edge states, their interplay with the pseudo-Landau levels is different for the armchair and zigzag ribbons. Finally, we study the effect of strain in the band structure of the Haldane model at the critical point of the topological transition, thus shedding light on the interplay between nontrivial topology and strain in quantum anomalous Hall systems.

  1. Fisheries management under nutrient influence

    DEFF Research Database (Denmark)

    Hammarlund, Cecilia; Nielsen, Max; Waldo, Staffan

    2018-01-01

    A fisheries management model that identifies the economic optimal management of fisheries under the influence of nutrients is presented. The model starts from the idea that growth in fish biomass increases with increasing availability of nutrients owing to higher food availability up to a peak......, after which growth falls due to eutrophication. The model is applied to Swedish and Danish cod fisheries in the Western Baltic Sea and identifies the welfare contribution of the fisheries, measured as the sum of resource rent and producer surplus. In 2010, the welfare contribution was −28......% of the landing value. Maximizing the model with respect to effort alone and additionally over nitrogen concentration increases the contribution to 11% of the landing value in 2010. The analysis shows that the welfare effect of reducing fishing effort through management reforms is large, but that the effect...

  2. Granular gases under extreme driving

    Science.gov (United States)

    Kang, W.; Machta, J.; Ben-Naim, E.

    2010-08-01

    We study inelastic gases in two dimensions using event-driven molecular-dynamics simulations. Our focus is the nature of the stationary state attained by rare injection of large amounts of energy to balance the dissipation due to collisions. We find that under such extreme driving, with the injection rate much smaller than the collision rate, the velocity distribution has a power-law high-energy tail. The numerically measured exponent characterizing this tail is in excellent agreement with predictions of kinetic theory over a wide range of system parameters. We conclude that driving by rare but powerful energy injection leads to a well-mixed gas and constitutes an alternative mechanism for agitating granular matter. In this distinct nonequilibrium steady state, energy cascades from large to small scales. Our simulations also show that when the injection rate is comparable with the collision rate, the velocity distribution has a stretched exponential tail.

  3. Precise object tracking under deformation

    International Nuclear Information System (INIS)

    Saad, M.H

    2010-01-01

    The precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This frame-work focuses on the precise object tracking under deformation such as scaling , rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high precession results.

  4. Physicists' Forced Migrations under Hitler

    Science.gov (United States)

    Beyerchen, Alan

    2011-03-01

    When the Nazis came to power in early 1933 they initiated formal and informal measures that forced Jews and political opponents from public institutions such as universities. Some physicists retired and others went into industry, but most emigrated. International communication and contact made emigration a viable option despite the desperate economic times in the Great Depression. Another wave of emigrations followed the annexation of Austria in 1938. Individual cases as well as general patterns of migration and adaptation to new environments will be examined in this presentation. One important result of the forced migrations was that many of the physicists expelled under Hitler played important roles in strengthening physics elsewhere, often on the Allied side in World War II.

  5. Rock strength under explosive loading

    International Nuclear Information System (INIS)

    Rimer, N.; Proffer, W.

    1993-01-01

    This presentation emphasizes the importance of a detailed description of the nonlinear deviatoric (strength) response of the surrounding rock in the numerical simulation of underground nuclear explosion phenomenology to the late times needed for test ban monitoring applications. We will show how numerical simulations which match ground motion measurements in volcanic tuffs and in granite use the strength values obtained from laboratory measurements on small core samples of these rocks but also require much lower strength values after the ground motion has interacted with the rock. The underlying physical mechanisms for the implied strength reduction are not yet well understood, and in fact may depend on the particular rock type. However, constitutive models for shock damage and/or effective stress have been used successfully at S-Cubed in both the Geophysics Program (primarily for DARPA) and the Containment Support Program (for DNA) to simulate late time ground motions measured at NTS in many different rock types

  6. Theory buried under heavy description

    Directory of Open Access Journals (Sweden)

    Vivian B. Martin Ph.D.

    2010-12-01

    Full Text Available In journalism when a reporter puts the main news or point of the story deep down in the text, we say she’s buried the lead, the lead being the main point of the story and usually the first paragraph. In Children in Genocide: extreme traumatization and affect regulation, psychoanalyst Suzanne Kaplan buries her theory. Her study of the after effects of trauma among Holocaust survivors who were children during their persecution and survivors of atrocities during the Rwandan atrocities of the 1990s, is filled with highly descriptive material from the many interviews that serve as data. An interesting grounded theory is peeking out from under all the disciplinary discourse and historical background one must read through to get to what grounded theory readers will consider the juicy parts: concepts on affect regulation in trauma survivors.

  7. Component processes underlying future thinking.

    Science.gov (United States)

    D'Argembeau, Arnaud; Ortoleva, Claudia; Jumentier, Sabrina; Van der Linden, Martial

    2010-09-01

    This study sought to investigate the component processes underlying the ability to imagine future events, using an individual-differences approach. Participants completed several tasks assessing different aspects of future thinking (i.e., fluency, specificity, amount of episodic details, phenomenology) and were also assessed with tasks and questionnaires measuring various component processes that have been hypothesized to support future thinking (i.e., executive processes, visual-spatial processing, relational memory processing, self-consciousness, and time perspective). The main results showed that executive processes were correlated with various measures of future thinking, whereas visual-spatial processing abilities and time perspective were specifically related to the number of sensory descriptions reported when specific future events were imagined. Furthermore, individual differences in self-consciousness predicted the subjective feeling of experiencing the imagined future events. These results suggest that future thinking involves a collection of processes that are related to different facets of future-event representation.

  8. Precise Object Tracking under Deformation

    International Nuclear Information System (INIS)

    Saad, M.H.

    2010-01-01

    The precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This framework focuses on the precise object tracking under deformation such as scaling, rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high precession results. xiiiThe precise object tracking is an essential issue in several serious applications such as; robot vision, automated surveillance (civil and military), inspection, biomedical image analysis, video coding, motion segmentation, human-machine interface, visualization, medical imaging, traffic systems, satellite imaging etc. This framework focuses on the precise object tracking under deformation such as scaling, rotation, noise, blurring and change of illumination. This research is a trail to solve these serious problems in visual object tracking by which the quality of the overall system will be improved. Developing a three dimensional (3D) geometrical model to determine the current pose of an object and predict its future location based on FIR model learned by the OLS. This framework presents a robust ranging technique to track a visual target instead of the traditional expensive ranging sensors. The presented research work is applied to real video stream and achieved high

  9. Nutrition security under extreme events

    Science.gov (United States)

    Martinez, A.

    2017-12-01

    Nutrition security under extreme events. Zero hunger being one of the Sustainable Development Goal from the United Nations, food security has become a trending research topic. However extreme events impact on global food security is not yet 100% understood and there is a lack of comprehension of the underlying mechanisms of global food trade and nutrition security to improve countries resilience to extreme events. In a globalized world, food is still a highly regulated commodity and a strategic resource. A drought happening in a net food-exporter will have little to no effect on its own population but the repercussion on net food-importers can be extreme. In this project, we propose a methodology to describe and quantify the impact of a local drought to human health at a global scale. For this purpose, nutrition supply and global trade data from FAOSTAT have been used with domestic food production from national agencies and FAOSTAT, global precipitation from the Climate Research Unit and health data from the World Health Organization. A modified Herfindahl-Hirschman Index (HHI) has been developed to measure the level of resilience of one country to a drought happening in another country. This index describes how a country is dependent of importation and how diverse are its importation. Losses of production and exportation due to extreme events have been calculated using yield data and a simple food balance at country scale. Results show that countries the most affected by global droughts are the one with the highest dependency to one exporting country. Changes induced by droughts also disturbed their domestic proteins, fat and calories supply resulting most of the time in a higher intake of calories or fat over proteins.

  10. Image annotation under X Windows

    Science.gov (United States)

    Pothier, Steven

    1991-08-01

    A mechanism for attaching graphic and overlay annotation to multiple bits/pixel imagery while providing levels of performance approaching that of native mode graphics systems is presented. This mechanism isolates programming complexity from the application programmer through software encapsulation under the X Window System. It ensures display accuracy throughout operations on the imagery and annotation including zooms, pans, and modifications of the annotation. Trade-offs that affect speed of display, consumption of memory, and system functionality are explored. The use of resource files to tune the display system is discussed. The mechanism makes use of an abstraction consisting of four parts; a graphics overlay, a dithered overlay, an image overly, and a physical display window. Data structures are maintained that retain the distinction between the four parts so that they can be modified independently, providing system flexibility. A unique technique for associating user color preferences with annotation is introduced. An interface that allows interactive modification of the mapping between image value and color is discussed. A procedure that provides for the colorization of imagery on 8-bit display systems using pixel dithering is explained. Finally, the application of annotation mechanisms to various applications is discussed.

  11. Noise exposure under hyperbaric conditions

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-03-01

    Objective evidence exists that divers demonstrate a hearing deficit greater than would be expected from ageing effects alone. Deafness in divers may be caused by a number of factors other than exposure to excessive noise levels, eg barotrauma, ear infection etc. This review concentrates on the concern that exposure of commercial divers to noise while at work may cause a hearing deficit. Sound pressure levels recorded both underwater and in diving chambers often exceed those allowable to workers onshore. However, the sound perceived by the diver is modified both in amplitude and in frequency when he is either underwater or in pressurised chambers. Broadly the effect of this modification is to attenuate the sound and thus offer some protection from high noise levels. The degree of attentuation varies with the frequency of the sound, however it is also possible under specific conditions associated with gas density for the sensitivity to particular frequencies to be amplified above that for normal atmospheric air. The levels of sound observed from some underwater tools are of concern even after allowing for a significant de-sensitisation of the divers` hearing. Reports of tinnitus and temporary hearing loss following a dive are sure signs that the noise levels have been harmful. It is not possible at present to describe risk criteria for hearing damage due to noise exposure associated with diving. (author)

  12. Reliability analysis under epistemic uncertainty

    International Nuclear Information System (INIS)

    Nannapaneni, Saideep; Mahadevan, Sankaran

    2016-01-01

    This paper proposes a probabilistic framework to include both aleatory and epistemic uncertainty within model-based reliability estimation of engineering systems for individual limit states. Epistemic uncertainty is considered due to both data and model sources. Sparse point and/or interval data regarding the input random variables leads to uncertainty regarding their distribution types, distribution parameters, and correlations; this statistical uncertainty is included in the reliability analysis through a combination of likelihood-based representation, Bayesian hypothesis testing, and Bayesian model averaging techniques. Model errors, which include numerical solution errors and model form errors, are quantified through Gaussian process models and included in the reliability analysis. The probability integral transform is used to develop an auxiliary variable approach that facilitates a single-level representation of both aleatory and epistemic uncertainty. This strategy results in an efficient single-loop implementation of Monte Carlo simulation (MCS) and FORM/SORM techniques for reliability estimation under both aleatory and epistemic uncertainty. Two engineering examples are used to demonstrate the proposed methodology. - Highlights: • Epistemic uncertainty due to data and model included in reliability analysis. • A novel FORM-based approach proposed to include aleatory and epistemic uncertainty. • A single-loop Monte Carlo approach proposed to include both types of uncertainties. • Two engineering examples used for illustration.

  13. Something New Under the Sun

    Science.gov (United States)

    Gavaghan, Helen

    In this, the first history of artifical satellites and their uses, Helen Gavaghan shows how the idea of putting an object in orbit around the earth changed from science fiction to indespensible technology in the twinkling of an eye. Thanks to satellites, we can now send data and images anywhere in the world in an instant. The satellite-based navigational system can pinpoint your exact location anywhere in the world; it is so precise that, from outer space, it can detect the sag on an airplane's wing. Focusing on three major areas of development - navigational satellites, communications, and weather observation and forecasting - Gavaghan tells the remarkable inside story of how obscure men and women, often laboring under strict secrecy, made the extraordinary scientific and technological discoveries needed to make these miracles happen. Written by a science journalist with support from the Sloane Foundation, the book describes the birth of the modern scientific era in the twentieth century, with creation of satellite technology. The narrative is part history - beginning with the Russian-U.S. contest with the launch of Sputnik; part politics, as scientists and visionary engineers compete for scarce funding that will bring their dreams to reality; partly the story of the singular and fascinating individuals who were present at the creation of our modern technological era.

  14. Pressure cylinders under fire condition

    Directory of Open Access Journals (Sweden)

    Jan Hora

    2016-03-01

    Full Text Available The presence of pressure cylinders under fire conditions significantly increases the risk rate for the intervening persons. It is considerably problematic to predict the pressure cylinders behaviour during heat exposition, its destruction progress and possible following explosion of the produced air–gas mixture because pressure cylinders and its environment generate a highly complicated dynamic system during an uncontrolled destruction. The large scale tests carried out by the Pilsen Fire and Rescue Department and the Rapid Response Unit of the Czech Republic Police in October 2012 and in May 2014 in the Military area Brdy and in the area of the former Lachema factory in Kaznějov had several objectives, namely, to record, qualify and quantify some of the aspects of an uncontrolled heat destruction procedure of an exposed pressure cylinder in an enclosed space and to qualify and describe the process of a controlled destruction of a pressure cylinder by shooting through it including basic tactical concepts. The article describes the experiments that were carried out.

  15. Decision Making Under Uncertain Categorization

    Directory of Open Access Journals (Sweden)

    Stephanie Ying-Fen Chen

    2014-09-01

    Full Text Available Two experiments investigated how category information is used in decision making under uncertainty and whether the framing of category information influences how it is used. Subjects were presented with vignettes in which the categorization of a critical item was ambiguous and were asked to choose among a set of actions with the goal of attaining the desired outcome for the main character in the story. The normative decision making strategy was to base the decision on all possible categories; however, research on a related topic, category-based induction, has found that people often only consider a single category when making predictions when categorization is uncertain. These experiments found that subjects tend to consider multiple categories when making decisions, but do so both when it is and is not appropriate, suggesting that use of multiple categories is not driven by an understanding of what categories are and are not relevant to the decision. Similarly, although a framing manipulation increased the rate of multiple-category use, it did so in situations in which multiple-category use was and was not appropriate.

  16. ATLAS: Now under new management

    CERN Multimedia

    Katarina Anthony

    2013-01-01

    On 1 March, the ATLAS Collaboration welcomed a new spokesperson, Dave Charlton (University of Birmingham), and two new deputy spokespersons, Thorsten Wengler (CERN) and Beate Heinemann (University of California, Berkeley and LBNL). The Bulletin takes a look at what’s in store for one of the world’s largest scientific collaborations.   ATLAS members at the 2010 collaboration meeting in Copenhagen. Image: Rune Johansen and Troels Petersen. ATLAS spokesperson Dave Charlton has seen the collaboration through countless milestones: from construction to start-up to the 4 July 2012 announcement, he’s been an integral part of the team. Now, after twelve years with the collaboration, Dave is moving into the main office for the next two years. “2012 was a landmark year for ATLAS,” says Dave. “We spent a lot of time in the limelight and, in many ways, all eyes are still on us. But with the shutdown now under way, our focus is ...

  17. Project Evaluation under Inflation Condition

    International Nuclear Information System (INIS)

    Hindy, M.; El Missiry, P.

    2004-01-01

    This paper analyzes the role of inflation in capital budgeting and attempts to introduce solutions to such implication in order to make the appropriate decision for the firm' stockholders under these circumstances. Inflation leads to biasness in evaluating the investment projects, due to its impact on the cash flow, the discount rate, the initial investment cost, and the depreciation. This paper has shown that the capital budgeting process is not neutral with respect to inflation, as the output prices will raise as well as the operating and capital expenditures will also be adjusted due to inflation. In addition, it has shown that it is reasonable to expect that the cost of capital will increase as a result of an increase in the real interest rate, the inflation premium, and the cost of equity. Of critical importance is the basis used in calculating the annual depreciation which may lead to the transfer of wealth from the investment projects to the government and will result in underestimating the net present value of the investment projects, if these depreciation charges is calculated based upon the historical values and not on the replacement cost of the fixed assets

  18. CANDU safety under severe accidents

    International Nuclear Information System (INIS)

    Snell, V.G.; Howieson, J.Q.; Alikhan, S.; Frescura, G.M.; King, F.; Rogers, J.T.; Tamm, H.

    1996-01-01

    The characteristics of the CANDU reactor relevant to severe accidents are set first by the inherent properties of the design, and second by the Canadian safety/licensing approach. The pressure-tube concept allows the separate, low-pressure, heavy-water moderator to act as a backup heat sink even if there is no water in the fuel channels. Should this also fail, the calandria shell itself can contain the debris, with heat being transferred to the water-filled shield tank around the core. Should the severe core damage sequence progress further, the shield tank and the concrete reactor vault significantly delay the challenge to containment. Furthermore, should core melt lead to containment overpressure, the containment behaviour is such that leaks through the concrete containment wall reduce the possibility of catastrophic structural failure. The Canadian licensing philosophy requires that each accident, together with failure of each safety system in turn, be assessed (and specified dose limits met) as part of the design and licensing basis. In response, designers have provided CANDUs with two independent dedicated shutdown systems, and the likelihood of Anticipated Transients Without Scram is negligible. Probabilistic safety assessment studies have been performed on operating CANDU plants, and on the 4 x 880 MW(e) Darlington station now under construction; furthermore a scoping risk assessment has been done for a CANDU 600 plant. They indicate that the summed severe core damage frequency is of the order of 5 x 10 -6 /year. 95 refs, 3 tabs

  19. CANDU safety under severe accidents

    International Nuclear Information System (INIS)

    Snell, V.G.; Howieson, J.Q.; Frescura, G.M.; King, F.; Rogers, J.T.; Tamm, H.

    1988-01-01

    The characteristics of the CANDU reactor relevant to severe accidents are set first by the inherent properties of the design, and second by the Canadian safety/licensing approach. Probabilistic safety assessment studies have been performed on operating CANDU plants, and on the 4 x 880 MW(e) Darlington station now under construction; furthermore a scoping risk assessment has been done for a CANDU 600 plant. They indicate that the summed severe core damage frequency is of the order of 5 x 10 -6 /year. CANDU nuclear plant designers and owner/operators share information and operational experience nationally and internationally through the CANDU Owners' Group (COG). The research program generally emphasizes the unique aspects of the CANDU concept, such as heat removal through the moderator, but it has also contributed significantly to areas generic to most power reactors such as hydrogen combustion, containment failure modes, fission product chemistry, and high temperature fuel behaviour. Abnormal plant operating procedures are aimed at first using event-specific emergency operating procedures, in cases where the event can be diagnosed. If this is not possible, generic procedures are followed to control Critical Safety Parameters and manage the accident. Similarly, the on-site contingency plans include a generic plan covering overall plant response strategy, and a specific plan covering each category of contingency

  20. German urologists under national socialism.

    Science.gov (United States)

    Krischel, Matthis

    2014-08-01

    The first full-time professorship for urology at a German university was established in 1937 and in 1942, a rare teaching qualification (Habilitation) for urology was granted, both at the prestigious Berlin University. At the same time, nearly a third of all physicians who worked in the field of urology were classified as "non-Aryan" according to Nazi race laws and were forced out of their profession and their homeland. Many of them committed suicide or, if they refused to flee, were murdered in concentration camps. German urologists also contributed to compulsory sterilization of men according to the "law for the prevention of hereditarily diseased offspring" between 1934 and 1945. Historical sources on the history of urology in Nazi Germany were reviewed and analyzed. These include textbooks and medical journals from the 1930s and 1940s, as well as files from different state and university archives. For urologists, the changing political environment in Germany after 1933 offered possibilities to assert their personal and professional interests. Unfortunately, in many cases, moral principles were thrown overboard, and physicians advanced their own careers and the specialty of urology at the expense of their patients and their Jewish colleagues. Under national socialism, German urologists backed Nazi health and race policies and in exchange gained further professionalization for their specialty, including university positions and increased independence from surgery. Only in recent years has this chapter of German urology's past become a topic of debate among members of the professional society.

  1. EDITORIAL: High performance under pressure High performance under pressure

    Science.gov (United States)

    Demming, Anna

    2011-11-01

    nanoelectromechanical systems. Researchers in China exploit the coupling between piezoelectric and semiconducting properties of ZnO in an optimised diode device design [6]. They used a Schottky rather than an ohmic contact to depress the off current. In addition they used ZnO nanobelts that have dominantly polar surfaces instead of [0001] ZnO nanowires to enhance the on current under the small applied forces obtained by using an atomic force microscopy tip. The nanobelts have potential for use in random access memory devices. Much of the success in applying piezoresistivity in device applications stems from a deepening understanding of the mechanisms behind the process. A collaboration of researchers in the USA and China have proposed a new criterion for identifying the carrier type of individual ZnO nanowires based on the piezoelectric output of a nanowire when it is mechanically deformed by a conductive atomic force microscopy tip in contact mode [7]. The p-type/n-type shell/core nanowires give positive piezoelectric outputs, while the n-type nanowires produce negative piezoelectric outputs. In this issue Zhong Lin Wang and colleagues in Italy and the US report theoretical investigations into the piezoresistive behaviour of ZnO nanowires for energy harvesting. The work develops previous research on the ability of vertically aligned ZnO nanowires under uniaxial compression to power a nanodevice, in particular a pH sensor [8]. Now the authors have used finite element simulations to study the system. Among their conclusions they find that, for typical geometries and donor concentrations, the length of the nanowire does not significantly influence the maximum output piezopotential because the potential mainly drops across the tip. This has important implications for low-cost, CMOS- and microelectromechanical-systems-compatible fabrication of nanogenerators. The simulations also reveal the influence of the dielectric surrounding the nanowire on the output piezopotential, especially for

  2. Vacuum mammotomy under ultrasound guidance

    International Nuclear Information System (INIS)

    Luczynska, E.; Kocurek, A.; Pawlik, T.; Aniol, J.; Herman, K.; Skotnicki, P.

    2007-01-01

    Breast ultrasound is a non-invasive method of breast examination. You can use it also for fine needle biopsy, core needle biopsy, vacuum mammotomy and for placing the '' wire '' before open surgical biopsy. 106 patients (105 women and 1 man) aged 20-71 years (mean age 46.9) were treated in Cancer Institute in Cracow by vacuum mammotomy under ultrasound guidance. The lesions found in ultrasonography were divided into three groups: benign lesions (BI RADS II), ambiguous lesions (BI RADS 0, III and IVa), and suspicious lesions (BI RADS IV B, IV C and V). Then lesions were qualified to vacuum mammotomy. According to USG, fibroadenoma or '' fibroadenoma-like '' lesions were found in 75 women, in 6 women complicated cysts, in 6 women cyst with dense fluid (to differentiate with FA), and in 19 patients undefined lesions. Fibroadenoma was confirmed in histopathology in 74% patients among patients with fibroadenoma or '' fibroadenoma-like '' lesions in ultrasound (in others also benign lesions were found). Among lesions undefined after ultrasound examination (total 27 patients) cancer was confirmed in 6 % (DCIS and IDC). In 6 patients with complicated cysts in ultrasound examination, histopathology confirmed fibroadenoma in 4 women, an intraductal lesion in 1 woman and inflamatory process in 1 woman. Also in 6 women with a dense cyst or fibroadenoma seen in ultrasound, histopathology confirmed fibroadenoma in 3 women and fibrosclerosis in 3 women. Any breast lesions undefined or suspicious after ultrasound examination should be verified. The method of verification or kind of operation of the whole lesion (vacuum mammotomy or '' wire '') depends on many factors, for example: lesion localization; lesion size; BI RADS category. (author)

  3. Superconducting critical temperature under pressure

    Science.gov (United States)

    González-Pedreros, G. I.; Baquero, R.

    2018-05-01

    The present record on the critical temperature of a superconductor is held by sulfur hydride (approx. 200 K) under very high pressure (approx. 56 GPa.). As a consequence, the dependence of the superconducting critical temperature on pressure became a subject of great interest and a high number of papers on of different aspects of this subject have been published in the scientific literature since. In this paper, we calculate the superconducting critical temperature as a function of pressure, Tc(P), by a simple method. Our method is based on the functional derivative of the critical temperature with the Eliashberg function, δTc(P)/δα2F(ω). We obtain the needed coulomb electron-electron repulsion parameter, μ*(P) at each pressure in a consistent way by fitting it to the corresponding Tc using the linearized Migdal-Eliashberg equation. This method requires as input the knowledge of Tc at the starting pressure only. It applies to superconductors for which the Migdal-Eliashberg equations hold. We study Al and β - Sn two weak-coupling low-Tc superconductors and Nb, the strong coupling element with the highest critical temperature. For Al, our results for Tc(P) show an excellent agreement with the calculations of Profeta et al. which are known to agree well with experiment. For β - Sn and Nb, we found a good agreement with the experimental measurements reported in several works. This method has also been applied successfully to PdH elsewhere. Our method is simple, computationally light and gives very accurate results.

  4. Structural Damage Assessment under Uncertainty

    Science.gov (United States)

    Lopez Martinez, Israel

    isolated based on the integration of sensitivity analysis and statistical sampling, which minimizes the occurrence of false-damage indication due to uncertainty. To perform diagnostic decision-making under uncertainty, an evidential reasoning approach for damage assessment is developed for addressing the possible imprecision in the damage localization results. The newly developed damage detection and localization techniques are applied and validated through both vibration test data from literature and in house laboratory experiments.

  5. Behaviour of uranium under irradiation

    International Nuclear Information System (INIS)

    Adda, Y.; Mustelier, J.P.; Quere, Y.; Commissariat a l'Energie Atomique, Fontenay-aux-Roses

    1964-01-01

    The main results obtained in a study of the formation of defects caused in uranium by fission at low temperature are reported. By irradiation at 20 K. it was possible to determine the number of Frenkel pairs produced by one fission. An analysis of the curves giving the variations in electrical resistivity shows the size of the displacement spikes and the mechanism of defect creation due to fission. Irradiations at 77 K gave additional information, showing behaviour differences in the case of recrystallised and of cold worked uranium. The diffusion of rare gases was studied using metal-rare gas alloys obtained by electrical discharge, and samples of irradiated uranium. Simple diffusion is only responsible for the release of the rare gases under vacuum in cases where the rare gas content is very low (very slightly irradiated U). On the other hand when the concentration is higher (samples prepared by electrical discharge) the gas is given off by the formation, growth and coalescence of bubbles; the apparent diffusion coefficient is then quite different from the true coefficient and cannot be used in calculations on swelling. The various factors governing the phenomenon of simple diffusion were examined. It was shown in particular that a small addition of molybdenum could reduce the diffusion coefficient by a factor of 100. The precipitation of gas in uranium (Kr), in silver (Kr) and in Al-Li alloy (He) have been followed by measurement of the crystal parameter and of the electrical resistivity, and by electron microscope examination of thin films. The important part played by dislocations in the generation and growth of bubbles has been demonstrated, and it has been shown also that precipitation of bubbles on the dislocation lattice could block the development of recrystallisation. The results of these studies were compared with observations made on the swelling of uranium and uranium alloys U Mo and U Nb strongly irradiated between 400 and 700 C. In the case of Cubic

  6. Science Underlying 2008 Nobel Prizes

    Science.gov (United States)

    Caldwell, Bernadette A.

    2009-01-01

    JCE offers a wealth of materials for teaching and learning chemistry that you can explore online. In the list below, Bernadette Caldwell of the Editorial Staff suggests additional resources that are available through JCE for teaching the science behind some of the 2008 Nobel Prizes . Discovering and Applying the Chemistry of GFP The Royal Swedish Academy of Sciences awarded the 2008 Nobel Prize in Chemistry for the discovery and development of the green fluorescent protein, GFP to three scientists: Osamu Shimomura, Martin Chalfie, and Roger Y. Tsien. These scientists led the field in discovering and introducing a fluorescing protein from jellyfish into cells and genes under study, which allows researchers to witness biochemistry in action. Now tags are available that emit light in different colors, revealing myriad biological processes and their interactions simultaneously. Identifying HPV and HIV, HIV's Replication Cycle, and HIV Virus-Host Interactions The Nobel Assembly at Karolinska Institutet awarded the 2008 Nobel Prize in Medicine or Physiology for their discovery of human immunodeficiency virus (HIV) to two scientists: Françoise Barré-Sinoussi and Luc Montagnier; and for his discovery of human papilloma viruses [HPV] causing cervical cancer to one scientist, Harald zur Hausen. Diseases caused by these infectious agents significantly affect global health. While isolating and studying the virus, researchers discovered HIV is an uncommon retrovirus that infects humans and relies on the host to make its viral DNA, infecting and killing the host's white blood cells, ultimately destroying the immune systems of infected humans. Related Resources at JCE Online The Journal has published articles relating to GFP specifically, and more generally to fluorescing compounds applied to biochemistry. The Journal has also published an article and a video on protease inhibition—a strategy to suppress HIV's biological processes. With the video clips, an accompanying guide

  7. Open hemorrhoidectomy under local anesthesia for symptomatic ...

    African Journals Online (AJOL)

    standard treatment for prolapsed hemorrhoids. The procedure is commonly done under general or regional anesthesia. This study is aimed to assess the feasibility and tolerability of open – hemorrhoidectomy under local anaesthesia in our setting.

  8. Optimal taxation of exhaustible resource under monopoly

    International Nuclear Information System (INIS)

    Im, Jeong-Bin

    2002-01-01

    This paper deals with the problem of using taxes (or subsidies) to correct the inefficient resource allocation under monopoly. In this paper, the question raised is 'what would be the optimal tax on resource extraction under monopoly?' Ultimately, it is shown that taxes may be devised to generate price and extraction paths under monopoly that are identical to those under the competitive equilibrium. Tax policy can thus be used as an instrument for changing the distortionary resource allocation generated by the monopolist

  9. Drug discrimination under a concurrent schedule.

    OpenAIRE

    Snodgrass, S H; McMillan, D E

    1996-01-01

    Three pigeons were trained to discriminate a 5.0 mg/kg dose of pentobarbital from saline under a two-key concurrent schedule with responding on the key associated with the presession injection, under both stimulus conditions, producing four times as many reinforcers as responding on the other key. This concurrent schedule resulted in approximately 70% responding to the higher reinforcement key under the pentobarbital stimulus and approximately 30% responding to that key under the saline stimu...

  10. Consistency of the MLE under mixture models

    OpenAIRE

    Chen, Jiahua

    2016-01-01

    The large-sample properties of likelihood-based statistical inference under mixture models have received much attention from statisticians. Although the consistency of the nonparametric MLE is regarded as a standard conclusion, many researchers ignore the precise conditions required on the mixture model. An incorrect claim of consistency can lead to false conclusions even if the mixture model under investigation seems well behaved. Under a finite normal mixture model, for instance, the consis...

  11. Metal speciation under Rhizophora and Avicennia mangles

    OpenAIRE

    Andrade, Regina Célia Bastos de; Patchineelam, Sambasiva Rao

    2000-01-01

    Speciation studies of Fe, Cr, Co, Ni and Cu on reactive fraction (adsorved on oxides, hydroxides, carbonates and clay minerals) and pyrite were performed in Avicennia schaueriana and Rhizophora mangle sediments from Amapá shoreline-Brazil. The soil under Avicennia showed a higher heavy metal concentration in reactive fraction than under Rhizophora. The soil under Rhizophora showed low heavy metal bioavailability, having an increasing association with pyrite across sediment section.

  12. Smith’s Economic Morals : An Introduction

    OpenAIRE

    Emmanuel S. de Dios

    2009-01-01

    This article introduces the moral philosophy underlying Smith's contributions to economics and emphasises the close connection between Smith's two principal works, the Theory of moral sentiments and the Wealth of nations.

  13. Performance tracking under ARCS contracts. Directive

    International Nuclear Information System (INIS)

    1992-01-01

    The directive discusses the development of a non-resource intensive method for reporting performance based work allocation results under the ARCS (Alternative Remedial Contracting Strategy) contractors

  14. Exchange rate policy under sovereign default risk

    OpenAIRE

    Schabert, Andreas

    2011-01-01

    We examine monetary policy options for a small open economy where sovereign default might occur due to intertemporal insolvency. Under interest rate policy and floating exchange rates the equilibrium is indetermined. Under a fixed exchange rate the equilibrium is uniquely determined and independent of sovereign default.

  15. Percutaneous nephrolithotripsy under assisted local anaesthesia for ...

    African Journals Online (AJOL)

    T.KH. Fathelbab

    Abstract. Objectives: The aim of the present study is to evaluate the feasibility and safety of performing PNL under local anesthesia in a selected group of patients who are at high risk for general anesthesia. Patients and methods: Forty seven patients underwent PNL under local anesthesia. There were 38 males.

  16. water infiltration, conductivity and runoff under fallow

    African Journals Online (AJOL)

    Measurements of runoff was done during the long rains of. 2003 and short rains of 2004. Infiltration was invariably higher under agroforestry systems (P<0.001) than sole cropping, particularly under Alnus and Calliandra systems. A similar pattern was observed for saturated hydraulic conductivity (Ksat), which was greater in ...

  17. Factors influencing immunisation coverage among children under ...

    African Journals Online (AJOL)

    Background This article explores the hypothesis that predisposing and enabling factors of households influence the vaccination status of the children under the age of five in Khartoum State, Sudan. Method The study was a cross-sectional survey among a representative sample of 410 male and female children under five ...

  18. Pavement behaviour under the super single tyre

    CSIR Research Space (South Africa)

    Viljoen, AW

    1982-06-01

    Full Text Available Pavement behaviour under the super single tyre (SST) was investigated and compared with that under a conventional dual tyre (CDT). Contact areas and contact pressures over a range of loading conditions were measured and compared. Two approaches were...

  19. Maximum likelihood estimation of exponential distribution under ...

    African Journals Online (AJOL)

    Maximum likelihood estimation of exponential distribution under type-ii censoring from imprecise data. ... Journal of Fundamental and Applied Sciences ... This paper deals with the estimation of exponential mean parameter under Type-II censoring scheme when the lifetime observations are fuzzy and are assumed to be ...

  20. Transformation kinetics of mixed polymeric substrates under ...

    African Journals Online (AJOL)

    Transformation kinetics of mixed polymeric substrates under transitory conditions by Aspergillus niger. ... Abstract. A mixture of polymeric substrates (simulating a complex wastewater) was transformed under sewer conditions and aerobiosis by Aspergillus niger in a tanks-in-series reactor at a hydraulic retention time of 14 h.

  1. Experiments were conducted under uniform flow

    Indian Academy of Sciences (India)

    First page Back Continue Last page Graphics. Experiments were conducted under uniform flow: Experiments were conducted under uniform flow: Bed slopes: S = 0.13, 0.30, 0.38%. Sediments used: d50 = 0.95, 2.6, 4.1 mm. Experimental conditions were independent of relative submergence: Sh (= d50/h) < 0.1 ...

  2. Mechanical buckling of artery under pulsatile pressure.

    Science.gov (United States)

    Liu, Qin; Han, Hai-Chao

    2012-04-30

    Tortuosity that often occurs in carotid and other arteries has been shown to be associated with high blood pressure, atherosclerosis, and other diseases. However the mechanisms of tortuosity development are not clear. Our previous studies have suggested that arteries buckling could be a possible mechanism for the initiation of tortuous shape but artery buckling under pulsatile flow condition has not been fully studied. The objectives of this study were to determine the artery critical buckling pressure under pulsatile pressure both experimentally and theoretically, and to elucidate the relationship of critical pressures under pulsatile flow, steady flow, and static pressure. We first tested the buckling pressures of porcine carotid arteries under these loading conditions, and then proposed a nonlinear elastic artery model to examine the buckling pressures under pulsatile pressure conditions. Experimental results showed that under pulsatile pressure arteries buckled when the peak pressures were approximately equal to the critical buckling pressures under static pressure. This was also confirmed by model simulations at low pulse frequencies. Our results provide an effective tool to predict artery buckling pressure under pulsatile pressure. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Capillary pressure studies under low gravity conditions.

    Science.gov (United States)

    Kovalchuk, V I; Ravera, F; Liggieri, L; Loglio, G; Pandolfini, P; Makievski, A V; Vincent-Bonnieu, S; Krägel, J; Javadi, A; Miller, R

    2010-12-15

    For the understanding of short-time adsorption phenomena and high-frequency relaxations at liquid interfaces particular experimental techniques are needed. The most suitable method for respective studies is the capillary pressure tensiometry. However, under gravity conditions there are rather strong limitations, in particular due to convections and interfacial deformations. This manuscript provides an overview of the state of the art of experimental tools developed for short-time and high-frequency investigations of liquid drops and bubbles under microgravity. Besides the brief description of instruments, the underlying theoretical basis will be presented and limits of the applied methods under ground and microgravity conditions will be discussed. The results on the role of surfactants under highly dynamic conditions will be demonstrated by some selected examples studied in two space shuttle missions on Discovery in 1998 and Columbia in 2003. Copyright © 2010 Elsevier B.V. All rights reserved.

  4. Phase transitions in solids under high pressure

    CERN Document Server

    Blank, Vladimir Davydovich

    2013-01-01

    Phase equilibria and kinetics of phase transformations under high pressureEquipment and methods for the study of phase transformations in solids at high pressuresPhase transformations of carbon and boron nitride at high pressure and deformation under pressurePhase transitions in Si and Ge at high pressure and deformation under pressurePolymorphic α-ω transformation in titanium, zirconium and zirconium-titanium alloys Phase transformations in iron and its alloys at high pressure Phase transformations in gallium and ceriumOn the possible polymorphic transformations in transition metals under pressurePressure-induced polymorphic transformations in АIBVII compoundsPhase transformations in AIIBVI and AIIIBV semiconductor compoundsEffect of pressure on the kinetics of phase transformations in iron alloysTransformations during deformation at high pressure Effects due to phase transformations at high pressureKinetics and hysteresis in high-temperature polymorphic transformations under pressureHysteresis and kineti...

  5. Combustion of emulsified fuel droplets under microgravity

    Science.gov (United States)

    Okajima, S.; Kanno, H.; Kumagai, S.

    Single-droplet experiments have been conducted under a zero-gravity condition in a freely falling chamber as a fundamental step of study on the spray combustion of hydrocarbon-water emulsified fuels. Such a behavior as the secondary micro-atomization was observed by taking schlieren photographs with a 35-mm movie camera installed on the falling assembly. Under zero gravity the emulsion droplet initiates steam discharge and puffing—that is, a mild atomization—at a time from ignition, but it does not lead to such a micro-explosion or disruption as is experienced under normal gravity. The apparent burning rate constant under zero gravity is about 30% smaller than that under normal gravity. These facts suggest that the internal convection in emulsion droplets plays an important role in causing the micro-explosion.

  6. Clock frequency estimation under spontaneous emission

    Science.gov (United States)

    Qin, Xi-Zhou; Huang, Jia-Hao; Zhong, Hong-Hua; Lee, Chaohong

    2018-02-01

    We investigate the quantum dynamics of a driven two-level system under spontaneous emission and its application in clock frequency estimation. By using the Lindblad equation to describe the system, we analytically obtain its exact solutions, which show three different regimes: Rabi oscillation, damped oscillation, and overdamped decay. From the analytical solutions, we explore how the spontaneous emission affects the clock frequency estimation. We find that under a moderate spontaneous emission rate, the transition frequency can still be inferred from the Rabi oscillation. Our results enable potential practical applications in frequency measurement and quantum control under decoherence.

  7. Polymers preparation under methane plasma environment

    International Nuclear Information System (INIS)

    Yang Wubao; Cai Zeyong; Zhao Zhen; Qi Lu

    2008-01-01

    Polymers are prepared under methane plasma environment, and appear to be white, slightly yellow, soft thread-like powders and floc under optical microscope. The polymers contain --CH 3 , -CH 2 , C-O, -C=C-,-OH etc. functional groups, but no simplex carbons. It is found that the solubility of this polymer is less than 0.1mg·ml -1 in different organic solvent. The productivity of the polymers is higher under a plasma environment with higher ionization, higher polarization of neutral gas, lower environment temperature and less permittivity. (authors)

  8. The German Physical Society Under National Socialism

    Science.gov (United States)

    Hoffmann, Dieter; Walker, Mark

    2004-12-01

    The history of the German Physical Society from 1933 to 1945 is not the same as a comprehensive history of physics under Adolf Hitler, but it does reflect important aspects of physicists' work and life during the Third Reich.

  9. Bottom Scour Observed Under Hurricane Ivan

    National Research Council Canada - National Science Library

    Teague, William J; Jarosz, Eva; Keen, Timothy R; Wang, David W; Hulbert, Mark S

    2006-01-01

    Observations that extensive bottom scour along the outer continental shelf under Hurricane Ivan resulted in the displacement of more than 100 million cubic meters of sediment from a 35x15 km region...

  10. Nuclides migration tests under deep geological conditions

    International Nuclear Information System (INIS)

    Kumata, M.; Vandergraaf, T.T.

    1991-01-01

    Migration behaviour of technetium and iodine under deep geological conditions was investigated by performing column tests under in-situ conditions at the 240 m level of the Underground Research Laboratory (URL) constructed in a granitic batholith near Pinawa, Manitoba, Canada. 131 I was injected with tritiated water into the column. Tritium and 131 I were eluted simultaneously. Almost 100 % of injected 131 I was recovered in the tritium breakthrough region, indicating that iodine moved through the column almost without retardation under experimental conditions. On the other hand, the injected technetium with tritium was strongly retarded in the column even though the groundwater was mildly reducing. Only about 7 % of injected 95m Tc was recovered in the tritium breakthrough region and the remaining fraction was strongly sorbed on the dark mafic minerals of column materials. This strong sorption of technetium on the column materials had not been expected from the results obtained from batch experiments carried out under anaerobic conditions. (author)

  11. Long term monitoring of moisture under pavements.

    Science.gov (United States)

    2010-01-01

    Monitoring of the environmental instrumentation installed under select pavement sections constructed : by the Ohio Department of Transportation (ODOT) in 1995 on US 23 in Delaware County, Ohio was : continued. The measurements made consisted of soil ...

  12. ROV dives under Great Lakes ice

    Science.gov (United States)

    Bolsenga, S.J.; Gannon, John E.; Kennedy, Gregory; Norton, D.C.; Herdendorf, Charles E.

    1989-01-01

    Observations of the underside of ice have a wide variety of applications. Severe under-ice roughness can affect ice movements, rough under-ice surfaces can scour the bottom disturbing biota and man-made structures such as pipelines, and the flow rate of rivers is often affected by under-ice roughness. A few reported observations of the underside of an ice cover have been made, usually by cutting a large block of ice and overturning it, by extensive boring, or by remote sensing. Such operations are extremely labor-intensive and, in some cases, prone to inaccuracies. Remotely operated vehicles (ROV) can partially solve these problems. In this note, we describe the use, performance in a hostile environment, and results of a study in which a ROV was deployed under the ice in Lake Erie (North American Great Lakes).

  13. CDC WONDER: Mortality - Underlying Cause of Death

    Data.gov (United States)

    U.S. Department of Health & Human Services — The CDC WONDER Mortality - Underlying Cause of Death online database is a county-level national mortality and population database spanning the years since 1979. Data...

  14. Nitrous Oxide flux measurements under various amendments

    Data.gov (United States)

    U.S. Environmental Protection Agency — The dataset consists of measurements of soil nitrous oxide emissions from soils under three different amendments: glucose, cellulose, and manure. Data includes the...

  15. Driving under the influence of cannabis.

    Science.gov (United States)

    2016-12-05

    As more states decriminalize and legalize medical and recreational use of cannabis (marijuana), traffic safety leaders and public health advocates have growing concerns about driving under the influence of cannabis (DUIC). How do we understand the cu...

  16. Object Construction Under Diverse Conditions of Rearing

    Science.gov (United States)

    Hunt, J. McVicker

    1974-01-01

    This study examines object construction and the ages at which children developing under various environmental conditions achieve five of the landmarks in the Uzgiris-Hunt (1974) scale of object permanence. (Author)

  17. Transformation kinetics of mixed polymeric substrates under ...

    African Journals Online (AJOL)

    bglucosidase and a-mannosidase were abundantly secreted in the growth medium. This research is the first report on mixed polymeric substrate biodegradation under sewer condition by A. niger, and could be considered as an open window on ...

  18. Fiscal Policy under Indeterminacy and Tax Evasion

    DEFF Research Database (Denmark)

    Busato, Francesco; Chiarini, Bruno; Marchetti, Enrico

    This paper shows under indeterminacy and tax evasion, an increase in corporate,labor or income tax rates pushes the economy into an expansionary pattern.These effects are reversed when the steady state is saddle-path stable.......This paper shows under indeterminacy and tax evasion, an increase in corporate,labor or income tax rates pushes the economy into an expansionary pattern.These effects are reversed when the steady state is saddle-path stable....

  19. Robust Satellite Communications Under Hostile Interference

    Science.gov (United States)

    2016-05-20

    or elimination of required feedback signals, jammer herding, multi-source signalling, and interference alignment . In the case of the replace with...AFRL-RV-PS- AFRL-RV-PS- TR-2016-0079 TR-2016-0079 ROBUST SATELLITE COMMUNICATIONS UNDER HOSTILE INTERFERENCE Marc Lichtman and Jeffrey Reed...FA9453-14-1-0222 Robust Satellite Communications Under Hostile Interference 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62601F 6. AUTHOR(S) 5d

  20. Analysis of ship deformation under sailing

    OpenAIRE

    Xiuwen, Shan; Lixiang, Sun; Yi, Pu; Chuncheng, Xu

    2018-01-01

    With the help of the three-dimensional potential flow theory and the hydrodynamic analysis of the loaded ship, the wave pressure distribution and the design wave parameters of the ship under loading conditions have been analyzed. Using the method of AQWA and ANSYS co-simulation, the stress level, stress distribution and deformation of the whole ship under loading conditions are obtained. The numerical analysis results can provide an effective basis for the assessment of ship navigation safety.