WorldWideScience

Sample records for modeling social network

  1. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  2. Brand marketing model on social networks

    OpenAIRE

    Jezukevičiūtė, Jolita; Davidavičienė, Vida

    2014-01-01

    Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...

  3. Brand Marketing Model on Social Networks

    Directory of Open Access Journals (Sweden)

    Jolita Jezukevičiūtė

    2014-04-01

    Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.

  4. Brand Marketing Model on Social Networks

    OpenAIRE

    Jolita Jezukevičiūtė; Vida Davidavičienė

    2014-01-01

    The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...

  5. Modeling online social signed networks

    Science.gov (United States)

    Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

    2018-04-01

    People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

  6. The model of social crypto-network

    Directory of Open Access Journals (Sweden)

    Марк Миколайович Орел

    2015-06-01

    Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks

  7. Modeling Epidemics Spreading on Social Contact Networks.

    Science.gov (United States)

    Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

    2015-09-01

    Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

  8. Settings in Social Networks : a Measurement Model

    NARCIS (Netherlands)

    Schweinberger, Michael; Snijders, Tom A.B.

    2003-01-01

    A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive

  9. Spatial Epidemic Modelling in Social Networks

    Science.gov (United States)

    Simoes, Joana Margarida

    2005-06-01

    The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

  10. Gossip spread in social network Models

    Science.gov (United States)

    Johansson, Tobias

    2017-04-01

    Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.

  11. Modelling Users` Trust in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Iacob Cătoiu

    2014-02-01

    Full Text Available Previous studies (McKnight, Lankton and Tripp, 2011; Liao, Lui and Chen, 2011 have shown the crucial role of trust when choosing to disclose sensitive information online. This is the case of online social networks users, who must disclose a certain amount of personal data in order to gain access to these online services. Taking into account privacy calculus model and the risk/benefit ratio, we propose a model of users’ trust in online social networks with four variables. We have adapted metrics for the purpose of our study and we have assessed their reliability and validity. We use a Partial Least Squares (PLS based structural equation modelling analysis, which validated all our initial assumptions, indicating that our three predictors (privacy concerns, perceived benefits and perceived risks explain 48% of the variation of users’ trust in online social networks, the resulting variable of our study. We also discuss the implications and further research opportunities of our study.

  12. Mathematical model for spreading dynamics of social network worms

    International Nuclear Information System (INIS)

    Sun, Xin; Liu, Yan-Heng; Han, Jia-Wei; Liu, Xue-Jie; Li, Bin; Li, Jin

    2012-01-01

    In this paper, a mathematical model for social network worm spreading is presented from the viewpoint of social engineering. This model consists of two submodels. Firstly, a human behavior model based on game theory is suggested for modeling and predicting the expected behaviors of a network user encountering malicious messages. The game situation models the actions of a user under the condition that the system may be infected at the time of opening a malicious message. Secondly, a social network accessing model is proposed to characterize the dynamics of network users, by which the number of online susceptible users can be determined at each time step. Several simulation experiments are carried out on artificial social networks. The results show that (1) the proposed mathematical model can well describe the spreading dynamics of social network worms; (2) weighted network topology greatly affects the spread of worms; (3) worms spread even faster on hybrid social networks

  13. Multiple Social Networks, Data Models and Measures for

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2017-01-01

    Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

  14. Modeling online social networks based on preferential linking

    International Nuclear Information System (INIS)

    Hu Hai-Bo; Chen Jun; Guo Jin-Li

    2012-01-01

    We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation, preferential acceptance, and preferential attachment. Based on the linear preference, we propose an analyzable model, which illustrates the mechanism of network growth and reproduces the process of network evolution. Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network. This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks

  15. A last updating evolution model for online social networks

    Science.gov (United States)

    Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui

    2013-05-01

    As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.

  16. Social network models predict movement and connectivity in ecological landscapes

    Science.gov (United States)

    Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  17. Social network models predict movement and connectivity in ecological landscapes.

    Science.gov (United States)

    Fletcher, Robert J; Acevedo, Miguel A; Reichert, Brian E; Pias, Kyle E; Kitchens, Wiley M

    2011-11-29

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  18. Modeling of contact tracing in social networks

    Science.gov (United States)

    Tsimring, Lev S.; Huerta, Ramón

    2003-07-01

    Spreading of certain infections in complex networks is effectively suppressed by using intelligent strategies for epidemic control. One such standard epidemiological strategy consists in tracing contacts of infected individuals. In this paper, we use a recently introduced generalization of the standard susceptible-infectious-removed stochastic model for epidemics in sparse random networks which incorporates an additional (traced) state. We describe a deterministic mean-field description which yields quantitative agreement with stochastic simulations on random graphs. We also discuss the role of contact tracing in epidemics control in small-world and scale-free networks. Effectiveness of contact tracing grows as the rewiring probability is reduced.

  19. Towards a Social Networks Model for Online Learning & Performance

    Science.gov (United States)

    Chung, Kon Shing Kenneth; Paredes, Walter Christian

    2015-01-01

    In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…

  20. An information spreading model based on online social networks

    Science.gov (United States)

    Wang, Tao; He, Juanjuan; Wang, Xiaoxia

    2018-01-01

    Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

  1. Modeling social networks in geographic space: approach and empirical application

    NARCIS (Netherlands)

    Arentze, T.A.; Berg, van den P.E.W.; Timmermans, H.J.P.

    2012-01-01

    Social activities are responsible for a large proportion of travel demands of individuals. Modeling of the social network of a studied population offers a basis to predict social travel in a more comprehensive way than currently is possible. In this paper we develop a method to generate a whole

  2. Modelling the impact of social network on energy savings

    International Nuclear Information System (INIS)

    Du, Feng; Zhang, Jiangfeng; Li, Hailong; Yan, Jinyue; Galloway, Stuart; Lo, Kwok L.

    2016-01-01

    Highlights: • Energy saving propagation along a social network is modelled. • This model consists of a time evolving weighted directed network. • Network weights and information decay are applied in savings calculation. - Abstract: It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout

  3. Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.

    Science.gov (United States)

    Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

    2016-01-01

    Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

  4. Model of community emergence in weighted social networks

    Science.gov (United States)

    Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.

    2009-04-01

    Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.

  5. Modeling the reemergence of information diffusion in social network

    Science.gov (United States)

    Yang, Dingda; Liao, Xiangwen; Shen, Huawei; Cheng, Xueqi; Chen, Guolong

    2018-01-01

    Information diffusion in networks is an important research topic in various fields. Existing studies either focus on modeling the process of information diffusion, e.g., independent cascade model and linear threshold model, or investigate information diffusion in networks with certain structural characteristics such as scale-free networks and small world networks. However, there are still several phenomena that have not been captured by existing information diffusion models. One of the prominent phenomena is the reemergence of information diffusion, i.e., a piece of information reemerges after the completion of its initial diffusion process. In this paper, we propose an optimized information diffusion model by introducing a new informed state into traditional susceptible-infected-removed model. We verify the proposed model via simulations in real-world social networks, and the results indicate that the model can reproduce the reemergence of information during the diffusion process.

  6. A growing social network model in geographical space

    Science.gov (United States)

    Antonioni, Alberto; Tomassini, Marco

    2017-09-01

    In this work we propose a new model for the generation of social networks that includes their often ignored spatial aspects. The model is a growing one and links are created either taking space into account, or disregarding space and only considering the degree of target nodes. These two effects can be mixed linearly in arbitrary proportions through a parameter. We numerically show that for a given range of the combination parameter, and for given mean degree, the generated network class shares many important statistical features with those observed in actual social networks, including the spatial dependence of connections. Moreover, we show that the model provides a good qualitative fit to some measured social networks.

  7. Perception of similarity: a model for social network dynamics

    International Nuclear Information System (INIS)

    Javarone, Marco Alberto; Armano, Giuliano

    2013-01-01

    Some properties of social networks (e.g., the mixing patterns and the community structure) appear deeply influenced by the individual perception of people. In this work we map behaviors by considering similarity and popularity of people, also assuming that each person has his/her proper perception and interpretation of similarity. Although investigated in different ways (depending on the specific scientific framework), from a computational perspective similarity is typically calculated as a distance measure. In accordance with this view, to represent social network dynamics we developed an agent-based model on top of a hyperbolic space on which individual distance measures are calculated. Simulations, performed in accordance with the proposed model, generate small-world networks that exhibit a community structure. We deem this model to be valuable for analyzing the relevant properties of real social networks. (paper)

  8. Analysis of organizational culture with social network models

    OpenAIRE

    Titov, S.

    2015-01-01

    Organizational culture is nowadays an object of numerous scientific papers. However, only marginal part of existing research attempts to use the formal models of organizational cultures. The lack of organizational culture models significantly limits the further research in this area and restricts the application of the theory to practice of organizational culture change projects. The article consists of general views on potential application of network models and social network analysis to th...

  9. Dynamic Evolution Model Based on Social Network Services

    Science.gov (United States)

    Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

    2013-11-01

    Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

  10. The communications model of using social network by sports clubs

    OpenAIRE

    S. Kowalski

    2012-01-01

    This article presents a model of marketing communications using social network by sports clubs. It presents the links between the sports club and its environment and uses of the Internet to promote it. The model of communication is composed of the elements responsible for the success of marketing in the web. Article also includes recommendations for using the model in practice.

  11. Modelling animal group fission using social network dynamics.

    Directory of Open Access Journals (Sweden)

    Cédric Sueur

    Full Text Available Group life involves both advantages and disadvantages, meaning that individuals have to compromise between their nutritional needs and their social links. When a compromise is impossible, the group splits in order to reduce conflict of interests and favour positive social interactions between its members. In this study we built a dynamic model of social networks to represent a succession of temporary fissions involving a change in social relations that could potentially lead to irreversible group fission (i.e. no more group fusion. This is the first study that assesses how a social network changes according to group fission-fusion dynamics. We built a model that was based on different parameters: the group size, the influence of nutritional needs compared to social needs, and the changes in the social network after a temporary fission. The results obtained from this theoretical data indicate how the percentage of social relation transfer, the number of individuals and the relative importance of nutritional requirements and social links influence the average number of days before irreversible fission occurs. The greater the nutritional needs and the higher the transfer of social relations during temporary fission, the fewer days will be observed before an irreversible fission. It is crucial to bridge the gap between the individual and the population level if we hope to understand how simple, local interactions may drive ecological systems.

  12. Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

    Directory of Open Access Journals (Sweden)

    Yunpeng Xiao

    2012-01-01

    Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

  13. An information search model for online social Networks - MOBIRSE

    Directory of Open Access Journals (Sweden)

    Miguel Angel Niño Zambrano

    2015-09-01

    Full Text Available Online Social Networks (OSNs have been gaining great importance among Internet users in recent years.  These are sites where it is possible to meet people, publish, and share content in a way that is both easy and free of charge. As a result, the volume of information contained in these websites has grown exponentially, and web search has consequently become an important tool for users to easily find information relevant to their social networking objectives. Making use of ontologies and user profiles can make these searches more effective. This article presents a model for Information Retrieval in OSNs (MOBIRSE based on user profile and ontologies which aims to improve the relevance of retrieved information on these websites. The social network Facebook was chosen for a case study and as the instance for the proposed model. The model was validated using measures such as At-k Precision and Kappa statistics, to assess its efficiency.

  14. Models, Entropy and Information of Temporal Social Networks

    Science.gov (United States)

    Zhao, Kun; Karsai, Márton; Bianconi, Ginestra

    Temporal social networks are characterized by heterogeneous duration of contacts, which can either follow a power-law distribution, such as in face-to-face interactions, or a Weibull distribution, such as in mobile-phone communication. Here we model the dynamics of face-to-face interaction and mobile phone communication by a reinforcement dynamics, which explains the data observed in these different types of social interactions. We quantify the information encoded in the dynamics of these networks by the entropy of temporal networks. Finally, we show evidence that human dynamics is able to modulate the information present in social network dynamics when it follows circadian rhythms and when it is interfacing with a new technology such as the mobile-phone communication technology.

  15. Studies on the population dynamics of a rumor-spreading model in online social networks

    Science.gov (United States)

    Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

    2018-02-01

    This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.

  16. k-Degree Anonymity Model for Social Network Data Publishing

    Directory of Open Access Journals (Sweden)

    MACWAN, K. R.

    2017-11-01

    Full Text Available Publicly accessible platform for social networking has gained special attraction because of its easy data sharing. Data generated on such social network is analyzed for various activities like marketing, social psychology, etc. This requires preservation of sensitive attributes before it becomes easily accessible. Simply removing the personal identities of the users before publishing data is not enough to maintain the privacy of the individuals. The structure of the social network data itself reveals much information regarding its users and their connections. To resolve this problem, k-degree anonymous method is adopted. It emphasizes on the modification of the graph to provide at least k number of nodes that contain the same degree. However, this approach is not efficient on a huge amount of social data and the modification of the original data fails to maintain data usefulness. In addition to this, the current anonymization approaches focus on a degree sequence-based graph model which leads to major modification of the graph topological properties. In this paper, we have proposed an improved k-degree anonymity model that retain the social network structural properties and also to provide privacy to the individuals. Utility measurement approach for community based graph model is used to verify the performance of the proposed technique.

  17. Stylized facts in social networks: Community-based static modeling

    Science.gov (United States)

    Jo, Hang-Hyun; Murase, Yohsuke; Török, János; Kertész, János; Kaski, Kimmo

    2018-06-01

    The past analyses of datasets of social networks have enabled us to make empirical findings of a number of aspects of human society, which are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations. Since the understanding of the structure of these complex social networks is far from complete, for deeper insight into human society more comprehensive datasets and modeling of the stylized facts are needed. Although the existing dynamical and static models can generate some stylized facts, here we take an alternative approach by devising a community-based static model with heterogeneous community sizes and larger communities having smaller link density and weight. With these few assumptions we are able to generate realistic social networks that show most stylized facts for a wide range of parameters, as demonstrated numerically and analytically. Since our community-based static model is simple to implement and easily scalable, it can be used as a reference system, benchmark, or testbed for further applications.

  18. Introducing serendipity in a social network model of knowledge diffusion

    International Nuclear Information System (INIS)

    Cremonini, Marco

    2016-01-01

    Highlights: • Serendipity as a control mechanism for knowledge diffusion in social network. • Local communication enhanced in the periphery of a network. • Prevalence of hub nodes in the network core mitigated. • Potential disruptive effect on network formation of uncontrolled serendipity. - Abstract: In this paper, we study serendipity as a possible strategy to control the behavior of an agent-based network model of knowledge diffusion. The idea of considering serendipity in a strategic way has been first explored in Network Learning and Information Seeking studies. After presenting the major contributions of serendipity studies to digital environments, we discuss the extension to our model: Agents are enriched with random topics for establishing new communication according to different strategies. The results show how important network properties could be influenced, like reducing the prevalence of hubs in the network’s core and increasing local communication in the periphery, similar to the effects of more traditional self-organization methods. Therefore, from this initial study, when serendipity is opportunistically directed, it appears to behave as an effective and applicable approach to social network control.

  19. Empirical Models of Social Learning in a Large, Evolving Network.

    Directory of Open Access Journals (Sweden)

    Ayşe Başar Bener

    Full Text Available This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals' access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1 attraction homophily causes individuals to form ties on the basis of attribute similarity, 2 aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3 social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends.

  20. Social Network Perspective: Model of Student Knowledge Sharing On Social Network Media

    OpenAIRE

    Bentar Priyopradono; Danny Manongga; Wiranto H. Utomo

    2012-01-01

    Recently, the role and development of information technology especially the internet, gives impact and influence in social relationship especially for social network site services users. The impact and influence the use of Internet which is related to exchange information and knowledge sharing still become one of the interesting topics to be researched. Now, the use of social media network by students are the best way to them to increase their knowledge as communication media such as, exchang...

  1. Energy model for rumor propagation on social networks

    Science.gov (United States)

    Han, Shuo; Zhuang, Fuzhen; He, Qing; Shi, Zhongzhi; Ao, Xiang

    2014-01-01

    With the development of social networks, the impact of rumor propagation on human lives is more and more significant. Due to the change of propagation mode, traditional rumor propagation models designed for word-of-mouth process may not be suitable for describing the rumor spreading on social networks. To overcome this shortcoming, we carefully analyze the mechanisms of rumor propagation and the topological properties of large-scale social networks, then propose a novel model based on the physical theory. In this model, heat energy calculation formula and Metropolis rule are introduced to formalize this problem and the amount of heat energy is used to measure a rumor’s impact on a network. Finally, we conduct track experiments to show the evolution of rumor propagation, make comparison experiments to contrast the proposed model with the traditional models, and perform simulation experiments to study the dynamics of rumor spreading. The experiments show that (1) the rumor propagation simulated by our model goes through three stages: rapid growth, fluctuant persistence and slow decline; (2) individuals could spread a rumor repeatedly, which leads to the rumor’s resurgence; (3) rumor propagation is greatly influenced by a rumor’s attraction, the initial rumormonger and the sending probability.

  2. How can social networks ever become complex? Modelling the emergence of complex networks from local social exchanges

    NARCIS (Netherlands)

    Pujol, Josep M.; Flache, Andreas; Delgado, Jordi; Sangüesa, Ramon; Sanguessa, R.

    2005-01-01

    Small-world and power-law network structures have been prominently proposed as models of large networks. However, the assumptions of these models usually-lack sociological grounding. We present a computational model grounded in social exchange theory. Agents search attractive exchange partners in a

  3. Visual social network analysis: effective approach to model complex human social, behaviour & culture.

    Science.gov (United States)

    Ahram, Tareq Z; Karwowski, Waldemar

    2012-01-01

    The advent and adoption of internet-based social networking has significantly altered our daily lives. The educational community has taken notice of the positive aspects of social networking such as creation of blogs and to support groups of system designers going through the same challenges and difficulties. This paper introduces a social networking framework for collaborative education, design and modeling of the next generation of smarter products and services. Human behaviour modeling in social networking application aims to ensure that human considerations for learners and designers have a prominent place in the integrated design and development of sustainable, smarter products throughout the total system lifecycle. Social networks blend self-directed learning and prescribed, existing information. The self-directed element creates interest within a learner and the ability to access existing information facilitates its transfer, and eventual retention of knowledge acquired.

  4. A hypergraph model of social tagging networks

    International Nuclear Information System (INIS)

    Zhang, Zi-Ke; Liu, Chuang

    2010-01-01

    The past few years have witnessed the great success of a new family of paradigms, so-called folksonomy, which allows users to freely associate tags with resources and efficiently manage them. In order to uncover the underlying structures and user behaviors in folksonomy, in this paper, we propose an evolutionary hypergraph model for explaining the emerging statistical properties. The present model introduces a novel mechanism that can not only assign tags to resources, but also retrieve resources via collaborative tags. We then compare the model with a real-world data set: Del.icio.us. Indeed, the present model shows considerable agreement with the empirical data in the following aspects: power-law hyperdegree distributions, negative correlation between clustering coefficients and hyperdegrees, and small average distances. Furthermore, the model indicates that most tagging behaviors are motivated by labeling tags on resources, and the tag plays a significant role in effectively retrieving interesting resources and making acquaintances with congenial friends. The proposed model may shed some light on the in-depth understanding of the structure and function of folksonomy

  5. Women’s Social Networks and Birth Attendant Decisions: Application of the Network-Episode Model

    OpenAIRE

    Edmonds, Joyce K.; Hruschka, Daniel; Bernard, H. Russell; Sibley, Lynn

    2011-01-01

    This paper examines the association of women's social networks with the use of skilled birth attendants in uncomplicated pregnancy and childbirth in Matlab, Bangladesh. The Network-Episode Model was applied to determine if network structure variables (density / kinship homogeneity / strength of ties) together with network content (endorsement for or against a particular type of birth attendant) explain the type of birth attendant used by women above and beyond the variance explained by women'...

  6. a Model for Brand Competition Within a Social Network

    Science.gov (United States)

    Huerta-Quintanilla, R.; Canto-Lugo, E.; Rodríguez-Achach, M.

    An agent-based model was built representing an economic environment in which m brands are competing for a product market. These agents represent companies that interact within a social network in which a certain agent persuades others to update or shift their brands; the brands of the products they are using. Decision rules were established that caused each agent to react according to the economic benefits it would receive; they updated/shifted only if it was beneficial. Each agent can have only one of the m possible brands, and she can interact with its two nearest neighbors and another set of agents which are chosen according to a particular set of rules in the network topology. An absorbing state was always reached in which a single brand monopolized the network (known as condensation). The condensation time varied as a function of model parameters is studied including an analysis of brand competition using different networks.

  7. Dynamic Trust Models between Users over Social Networks

    Science.gov (United States)

    2016-03-30

    SUPPLEMENTARY NOTES 14. ABSTRACT In this project, by focusing on a number of word -of- mouth communication websites, we attempted to...analyzed evolution of trust networks in social media sites from a perspective of mediators. To this end, we proposed two stochastic models that...focusing on a number of word -of- mouth communication websites, we first attempt to construct dynamic trust models between users that enable to explain trust

  8. A rumor transmission model with incubation in social networks

    Science.gov (United States)

    Jia, Jianwen; Wu, Wenjiang

    2018-02-01

    In this paper, we propose a rumor transmission model with incubation period and constant recruitment in social networks. By carrying out an analysis of the model, we study the stability of rumor-free equilibrium and come to the local stable condition of the rumor equilibrium. We use the geometric approach for ordinary differential equations for showing the global stability of the rumor equilibrium. And when ℜ0 = 1, the new model occurs a transcritical bifurcation. Furthermore, numerical simulations are used to support the analysis. At last, some conclusions are presented.

  9. Social networks

    CERN Document Server

    Etaner-Uyar, A Sima

    2014-01-01

    The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many

  10. TRUST MODEL FOR SOCIAL NETWORK USING SINGULAR VALUE DECOMPOSITION

    Directory of Open Access Journals (Sweden)

    Davis Bundi Ntwiga

    2016-06-01

    Full Text Available For effective interactions to take place in a social network, trust is important. We model trust of agents using the peer to peer reputation ratings in the network that forms a real valued matrix. Singular value decomposition discounts the reputation ratings to estimate the trust levels as trust is the subjective probability of future expectations based on current reputation ratings. Reputation and trust are closely related and singular value decomposition can estimate trust using the real valued matrix of the reputation ratings of the agents in the network. Singular value decomposition is an ideal technique in error elimination when estimating trust from reputation ratings. Reputation estimation of trust is optimal at the discounting of 20 %.

  11. Modeling the cooperative and competitive contagions in online social networks

    Science.gov (United States)

    Zhuang, Yun-Bei; Chen, J. J.; Li, Zhi-hong

    2017-10-01

    The wide adoption of social media has increased the interaction among different pieces of information, and this interaction includes cooperation and competition for our finite attention. While previous research focus on fully competition, this paper extends the interaction to be both "cooperation" and "competition", by employing an IS1S2 R model. To explore how two different pieces of information interact with each other, the IS1S2 R model splits the agents into four parts-(Ignorant-Spreader I-Spreader II-Stifler), based on SIR epidemic spreading model. Using real data from Weibo.com, a social network site similar to Twitter, we find some parameters, like decaying rates, can both influence the cooperative diffusion process and the competitive process, while other parameters, like infectious rates only have influence on the competitive diffusion process. Besides, the parameters' effect are more significant in the competitive diffusion than in the cooperative diffusion.

  12. Models of Charity Donations and Project Funding in Social Networks

    Science.gov (United States)

    Wojciechowski, Adam

    One of the key fundaments of building a society is common interest or shared aims of the group members. This research work is a try to analyze web-based services oriented towards money collection for various social and charity projects. The phenomenon of social founding is worth a closer look at because its success strongly depends on the ability to build an ad-hoc or persistent groups of people sharing their believes and willing to support external institutions or individuals. The paper presents a review of money collection sites, various models of donation and money collection process as well as ways how the projects' results are reported to their founders. There is also a proposal of money collection service, where donators are not charged until total declared help overheads required resources to complete the project. The risk of missing real donations for declared payments, after the collection is closed, can be assessed and minimized by building a social network.

  13. A Temporal-Causal Modelling Approach to Integrated Contagion and Network Change in Social Networks

    NARCIS (Netherlands)

    Blankendaal, Romy; Parinussa, Sarah; Treur, Jan

    2016-01-01

    This paper introduces an integrated temporal-causal model for dynamics in social networks addressing the contagion principle by which states are affected mutually, and both the homophily principle and the more-becomes-more principle by which connections are adapted over time. The integrated model

  14. Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

    Science.gov (United States)

    Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

    2016-01-01

    Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

  15. Nonlinear model of epidemic spreading in a complex social network.

    Science.gov (United States)

    Kosiński, Robert A; Grabowski, A

    2007-10-01

    The epidemic spreading in a human society is a complex process, which can be described on the basis of a nonlinear mathematical model. In such an approach the complex and hierarchical structure of social network (which has implications for the spreading of pathogens and can be treated as a complex network), can be taken into account. In our model each individual has one of the four permitted states: susceptible, infected, infective, unsusceptible or dead. This refers to the SEIR model used in epidemiology. The state of an individual changes in time, depending on the previous state and the interactions with other individuals. The description of the interpersonal contacts is based on the experimental observations of the social relations in the community. It includes spatial localization of the individuals and hierarchical structure of interpersonal interactions. Numerical simulations were performed for different types of epidemics, giving the progress of a spreading process and typical relationships (e.g. range of epidemic in time, the epidemic curve). The spreading process has a complex and spatially chaotic character. The time dependence of the number of infective individuals shows the nonlinear character of the spreading process. We investigate the influence of the preventive vaccinations on the spreading process. In particular, for a critical value of preventively vaccinated individuals the percolation threshold is observed and the epidemic is suppressed.

  16. Using attractiveness model for actors ranking in social media networks.

    Science.gov (United States)

    Qasem, Ziyaad; Jansen, Marc; Hecking, Tobias; Hoppe, H Ulrich

    2017-01-01

    Influential actors detection in social media such as Twitter or Facebook can play a major role in gathering opinions on particular topics, improving the marketing efficiency, predicting the trends, etc. This work aims to extend our formally defined T measure to present a new measure aiming to recognize the actor's influence by the strength of attracting new important actors into a networked community. Therefore, we propose a model of the actor's influence based on the attractiveness of the actor in relation to the number of other attractors with whom he/she has established connections over time. Using an empirically collected social network for the underlying graph, we have applied the above-mentioned measure of influence in order to determine optimal seeds in a simulation of influence maximization. We study our extended measure in the context of information diffusion because this measure is based on a model of actors who attract others to be active members in a community. This corresponds to the idea of the IC simulation model which is used to identify the most important spreaders in a set of actors.

  17. Social Sensor Analytics: Making Sense of Network Models in Social Media

    Energy Technology Data Exchange (ETDEWEB)

    Dowling, Chase P.; Harrison, Joshua J.; Sathanur, Arun V.; Sego, Landon H.; Corley, Courtney D.

    2015-07-27

    Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013 and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.

  18. Social networks and trade of services: modelling interregional flows with spatial and network autocorrelation effects

    Science.gov (United States)

    de la Mata, Tamara; Llano, Carlos

    2013-07-01

    Recent literature on border effect has fostered research on informal barriers to trade and the role played by network dependencies. In relation to social networks, it has been shown that intensity of trade in goods is positively correlated with migration flows between pairs of countries/regions. In this article, we investigate whether such a relation also holds for interregional trade of services. We also consider whether interregional trade flows in services linked with tourism exhibit spatial and/or social network dependence. Conventional empirical gravity models assume the magnitude of bilateral flows between regions is independent of flows to/from regions located nearby in space, or flows to/from regions related through social/cultural/ethic network connections. With this aim, we provide estimates from a set of gravity models showing evidence of statistically significant spatial and network (demographic) dependence in the bilateral flows of the trade of services considered. The analysis has been applied to the Spanish intra- and interregional monetary flows of services from the accommodation, restaurants and travel agencies for the period 2000-2009, using alternative datasets for the migration stocks and definitions of network effects.

  19. Projecting the Mental Model of Social Networking Site Usage

    Directory of Open Access Journals (Sweden)

    Chun-Hui Wu

    2018-01-01

    Full Text Available The growth of online social networking sites (SNS has created a new world of connection and communication for online users. SNS usage has become an important part of people’s daily lives. This study aims to obtain new insights towards SNS usage behaviour. Based on participants’ mental models, it is hoped to make more clear exposition about their perceptions and experiences as well as to explore what factors affect their behaviour for using social networking sites. A blend of qualitative methodologies was adopted for data collection and analysis, including the Zaltman metaphor elicitation technique (ZMET method, the laddering technique, and the means-end chain theory. The results of this study show that the most important values of using SNS include its convenience, maintaining relationship, gaining relaxation, as well as reaching coherence. Additionally, participants pointed out they cared about their online privacy issues very much and had found some potential dangers; however, they continued to use these sites because of the great benefits and enjoyment.

  20. Opinion formation models in static and dynamic social networks

    Science.gov (United States)

    Singh, Pramesh

    We study models of opinion formation on static as well as dynamic networks where interaction among individuals is governed by widely accepted social theories. In particular, three models of competing opinions based on distinct interaction mechanisms are studied. A common feature in all of these models is the existence of a tipping point in terms of a model parameter beyond which a rapid consensus is reached. In the first model that we study on a static network, a node adopts a particular state (opinion) if a threshold fraction of its neighbors are already in that state. We introduce a few initiator nodes which are in state '1' in a population where every node is in state '0'. Thus, opinion '1' spreads through the population until no further influence is possible. Size of the spread is greatly affected by how these initiator nodes are selected. We find that there exists a critical fraction of initiators pc that is needed to trigger global cascades for a given threshold phi. We also study heuristic strategies for selecting a set of initiator nodes in order to maximize the cascade size. The structural properties of networks also play an important role in the spreading process. We study how the dynamics is affected by changing the clustering in a network. It turns out that local clustering is helpful in spreading. Next, we studied a model where the network is dynamic and interactions are homophilic. We find that homophily-driven rewiring impedes the reaching of consensus and in the absence of committed nodes (nodes that are not influenceable on their opinion), consensus time Tc diverges exponentially with network size N . As we introduce a fraction of committed nodes, beyond a critical value, the scaling of Tc becomes logarithmic in N. We also find that slight change in the interaction rule can produce strikingly different scaling behaviors of T c . However, introducing committed agents in the system drastically improves the scaling of the consensus time regardless of

  1. Fuzzy Modelling for Human Dynamics Based on Online Social Networks.

    Science.gov (United States)

    Cuenca-Jara, Jesus; Terroso-Saenz, Fernando; Valdes-Vela, Mercedes; Skarmeta, Antonio F

    2017-08-24

    Human mobility mining has attracted a lot of attention in the research community due to its multiple implications in the provisioning of innovative services for large metropolises. In this scope, Online Social Networks (OSN) have arisen as a promising source of location data to come up with new mobility models. However, the human nature of this data makes it rather noisy and inaccurate. In order to deal with such limitations, the present work introduces a framework for human mobility mining based on fuzzy logic. Firstly, a fuzzy clustering algorithm extracts the most active OSN areas at different time periods. Next, such clusters are the building blocks to compose mobility patterns. Furthermore, a location prediction service based on a fuzzy rule classifier has been developed on top of the framework. Finally, both the framework and the predictor has been tested with a Twitter and Flickr dataset in two large cities.

  2. Network-Oriented Modeling of Multi-Criteria Homophily and Opinion Dynamics in Social Media

    NARCIS (Netherlands)

    Kozyreva, Olga; Pechina, Anna; Treur, J.

    2018-01-01

    In this paper we model the opinion dynamics in social groups in combination with adaptation of the connections based on a multicriteria homophily principle. The adaptive network model has been designed according to a Network-Oriented Modeling approach based on temporal-causal networks. The model has

  3. Popularity Evaluation Model for Microbloggers Online Social Network

    Directory of Open Access Journals (Sweden)

    Xia Zhang

    2014-01-01

    Full Text Available Recently, microblogging is widely studied by the researchers in the domain of the online social network (OSN. How to evaluate the popularities of microblogging users is an important research field, which can be applied to commercial advertising, user behavior analysis and information dissemination, and so forth. Previous studies on the evaluation methods cannot effectively solve and accurately evaluate the popularities of the microbloggers. In this paper, we proposed an electromagnetic field theory based model to analyze the popularities of microbloggers. The concept of the source in microblogging field is first put forward, which is based on the concept of source in the electromagnetic field; then, one’s microblogging flux is calculated according to his/her behaviors (send or receive feedbacks on the microblogging platform; finally, we used three methods to calculate one’s microblogging flux density, which can represent one’s popularity on the microblogging platform. In the experimental work, we evaluated our model using real microblogging data and selected the best one from the three popularity measure methods. We also compared our model with the classic PageRank algorithm; and the results show that our model is more effective and accurate to evaluate the popularities of the microbloggers.

  4. Mental Health, School Problems, and Social Networks: Modeling Urban Adolescent Substance Use

    Science.gov (United States)

    Mason, Michael J.

    2010-01-01

    This study tested a mediation model of the relationship with school problems, social network quality, and substance use with a primary care sample of 301 urban adolescents. It was theorized that social network quality (level of risk or protection in network) would mediate the effects of school problems, accounting for internalizing problems and…

  5. Modeling the Propagation of Trojan Malware in Online Social Networks

    OpenAIRE

    Faghani, Mohammad Reza; Nugyen, Uyen Trang

    2017-01-01

    The popularity and widespread usage of online social networks (OSN) have attracted cyber criminals who have used OSNs as a platform to spread malware. Among different types of malware in OSNs, Trojan is the most popular type with hundreds of attacks on OSN users in the past few years. Trojans infecting a user's computer have the ability to steal confidential information, install ransomware and infect other computers in the network. Therefore, it is important to understand propagation dynamics...

  6. SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

    International Nuclear Information System (INIS)

    Dong Suyalatu; Deng Yan-Bin; Huang Yong-Chang

    2017-01-01

    Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network . (paper)

  7. SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

    Science.gov (United States)

    Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

    2017-10-01

    Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028

  8. The specification of weight structures in network autocorrelation models of social influence

    NARCIS (Netherlands)

    Leenders, Roger Th.A.J.

    2002-01-01

    Many physical and social phenomena are embedded within networks of interdependencies, the so-called 'context' of these phenomena. In network analysis, this type of process is typically modeled as a network autocorrelation model. Parameter estimates and inferences based on autocorrelation models,

  9. A game theory-based trust measurement model for social networks.

    Science.gov (United States)

    Wang, Yingjie; Cai, Zhipeng; Yin, Guisheng; Gao, Yang; Tong, Xiangrong; Han, Qilong

    2016-01-01

    In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.

  10. Social Content Recommendation Based on Spatial-Temporal Aware Diffusion Modeling in Social Networks

    Directory of Open Access Journals (Sweden)

    Farman Ullah

    2016-09-01

    Full Text Available User interactions in online social networks (OSNs enable the spread of information and enhance the information dissemination process, but at the same time they exacerbate the information overload problem. In this paper, we propose a social content recommendation method based on spatial-temporal aware controlled information diffusion modeling in OSNs. Users interact more frequently when they are close to each other geographically, have similar behaviors, and fall into similar demographic categories. Considering these facts, we propose multicriteria-based social ties relationship and temporal-aware probabilistic information diffusion modeling for controlled information spread maximization in OSNs. The proposed social ties relationship modeling takes into account user spatial information, content trust, opinion similarity, and demographics. We suggest a ranking algorithm that considers the user ties strength with friends and friends-of-friends to rank users in OSNs and select highly influential injection nodes. These nodes are able to improve social content recommendations, minimize information diffusion time, and maximize information spread. Furthermore, the proposed temporal-aware probabilistic diffusion process categorizes the nodes and diffuses the recommended content to only those users who are highly influential and can enhance information dissemination. The experimental results show the effectiveness of the proposed scheme.

  11. Fitting Social Network Models Using Varying Truncation Stochastic Approximation MCMC Algorithm

    KAUST Repository

    Jin, Ick Hoon; Liang, Faming

    2013-01-01

    The exponential random graph model (ERGM) plays a major role in social network analysis. However, parameter estimation for the ERGM is a hard problem due to the intractability of its normalizing constant and the model degeneracy. The existing

  12. An agent-based model of centralized institutions, social network technology, and revolution.

    Science.gov (United States)

    Makowsky, Michael D; Rubin, Jared

    2013-01-01

    This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change.

  13. Self-Concealment, Social Network Sites Usage, Social Appearance Anxiety, Loneliness of High School Students: A Model Testing

    Science.gov (United States)

    Dogan, Ugur; Çolak, Tugba Seda

    2016-01-01

    This study was tested a model for explain to social networks sites (SNS) usage with structural equation modeling (SEM). Using SEM on a sample of 475 high school students (35% male, 65% female) students, model was investigated the relationship between self-concealment, social appearance anxiety, loneliness on SNS such as Twitter and Facebook usage.…

  14. Appplication of statistical mechanical methods to the modeling of social networks

    Science.gov (United States)

    Strathman, Anthony Robert

    With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

  15. Rumor Spreading Model with Trust Mechanism in Complex Social Networks

    International Nuclear Information System (INIS)

    Wang Ya-Qi; Yang Xiao-Yuan; Han Yi-Liang; Wang Xu-An

    2013-01-01

    In this paper, to study rumor spreading, we propose a novel susceptible-infected-removed (SIR) model by introducing the trust mechanism. We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks. Then a steady-state analysis is conducted to investigate the critical threshold and the final size of the rumor spreading. We show that the introduction of trust mechanism reduces the final rumor size and the velocity of rumor spreading, but increases the critical thresholds on both networks. Moreover, the trust mechanism not only greatly reduces the maximum rumor influence, but also postpones the rumor terminal time, which provides us with more time to take measures to control the rumor spreading. The theoretical results are confirmed by sufficient numerical simulations. (interdisciplinary physics and related areas of science and technology)

  16. Rumor Spreading Model with Trust Mechanism in Complex Social Networks

    Science.gov (United States)

    Wang, Ya-Qi; Yang, Xiao-Yuan; Han, Yi-Liang; Wang, Xu-An

    2013-04-01

    In this paper, to study rumor spreading, we propose a novel susceptible-infected-removed (SIR) model by introducing the trust mechanism. We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks. Then a steady-state analysis is conducted to investigate the critical threshold and the final size of the rumor spreading. We show that the introduction of trust mechanism reduces the final rumor size and the velocity of rumor spreading, but increases the critical thresholds on both networks. Moreover, the trust mechanism not only greatly reduces the maximum rumor influence, but also postpones the rumor terminal time, which provides us with more time to take measures to control the rumor spreading. The theoretical results are confirmed by sufficient numerical simulations.

  17. PERSON IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Андрей Борисович Шалимов

    2013-11-01

    Full Text Available Purpose: Our scientific purpose is creation of practical model of person’s representation in social networks (Facebook, Twitter, Classmates. As user of social networks, person is made conditional not only upon its own identity, but also upon the information about himself, which he is ready to share with his friends in contact list. Goal-setting and practical activities for their achievement mean that you should apply force, it can completely eliminates systemic factors, the system of power relations, which overwhelms human being in social networks.Methodology: The reconstruction of the model of human in the popularity of social networksResults: There is descripton of practical model of person's representation in social networks, it includes the management of own identity and the audience (the list of contacts. When person manages own identity, he answers the question, «Whom I can dare to be?». Person perceives himself in social networks' being, he understands himself and his place in the world, he identifies.Managing the way in social media means that you answer the question «What I want to tell?». Person in social media looks at events in the field of culture, economy, politics, social relations through the prism of his own attitudes, he forms and formulates his own agenda and he is going to tell about himself through them.Practical implications: Everyday people’s life, practical activities, including marketing in social networks.DOI: http://dx.doi.org/10.12731/2218-7405-2013-9-51

  18. HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP MODEL

    Directory of Open Access Journals (Sweden)

    Chun Meng Tang

    2015-12-01

    Full Text Available Social networking sites are popular among university students, and students today are indeed spoiled for choice. New emerging social networking sites sprout up amid popular sites, while some existing ones die out. Given the choice of so many social networking sites, how do students decide which one they will sign up for and stay on as an active user? The answer to this question is of interest to social networking site designers and marketers. The market of social networking sites is highly competitive. To maintain the current user base and continue to attract new users, how should social networking sites design their sites? Marketers spend a fairly large percent of their marketing budget on social media marketing. To formulate an effective social media strategy, how much do marketers understand the users of social networking sites? Learning from website evaluation studies, this study intends to provide some answers to these questions by examining how university students decide between two popular social networking sites, Facebook and Twitter. We first developed an analytic hierarchy process (AHP model of four main selection criteria and 12 sub-criteria, and then administered a questionnaire to a group of university students attending a course at a Malaysian university. AHP analyses of the responses from 12 respondents provided an insight into the decision-making process involved in students’ selection of social networking sites. It seemed that of the four main criteria, privacy was the top concern, followed by functionality, usability, and content. The sub-criteria that were of key concern to the students were apps, revenue-generating opportunities, ease of use, and information security. Between Facebook and Twitter, the students thought that Facebook was the better choice. This information is useful for social networking site designers to design sites that are more relevant to their users’ needs, and for marketers to craft more effective

  19. Local Social Networks

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Sørensen, Lene Tolstrup

    2011-01-01

    Online social networks have become essential for many users in their daily communication. Through a combination of the online social networks with opportunistic networks, a new concept arises: Local Social Networks. The target of local social networks is to promote social networking benefits...... in physical environment in order to leverage personal affinities in the users' surroundings. The purpose of this paper is to present and discuss the concept of local social networks as a new social communication system. Particularly, the preliminary architecture and the prototype of local social networks...

  20. COSMODEL: AN INTERACTION MODEL FOR SOCIAL NETWORK GAMES

    Directory of Open Access Journals (Sweden)

    MIGUEL NIÑO

    2011-01-01

    Full Text Available Los juegos para redes sociales (videojuegos para redes sociales en línea, se han vuelto muy populares entre los desarrolladores de videojuegos. Sin embargo, los soportes conceptuales para los diseñadores de este tipo de juegos son escasos, en particular aquellos que se enfocan en la interacción entre jugadores. Debido a lo anterior, se propone CosModel como un modelo para el diseño de juegos para redes sociales. CosModel se compone de tres vistas de diseño de interacción que respaldan la construcción de estos juegos y se enfocan en potenciar las interacciones entre los jugadores. Una de estas vistas presenta el uso de una metáfora como ayuda conceptual para el diseño de juegos para redes sociales. Este artículo presenta el contexto teórico que apoya al modelo, el proceso de desarrollo del modelo y su estructura, y un proceso propuesto para su implementación.

  1. Systems approach to studying animal sociality: individual position versus group organization in dynamic social network models.

    Directory of Open Access Journals (Sweden)

    Karlo Hock

    2010-12-01

    Full Text Available Social networks can be used to represent group structure as a network of interacting components, and also to quantify both the position of each individual and the global properties of a group. In a series of simulation experiments based on dynamic social networks, we test the prediction that social behaviors that help individuals reach prominence within their social group may conflict with their potential to benefit from their social environment. In addition to cases where individuals were able to benefit from improving both their personal relative importance and group organization, using only simple rules of social affiliation we were able to obtain results in which individuals would face a trade-off between these factors. While selection would favor (or work against social behaviors that concordantly increase (or decrease, respectively fitness at both individual and group level, when these factors conflict with each other the eventual selective pressure would depend on the relative returns individuals get from their social environment and their position within it. The presented results highlight the importance of a systems approach to studying animal sociality, in which the effects of social behaviors should be viewed not only through the benefits that those provide to individuals, but also in terms of how they affect broader social environment and how in turn this is reflected back on an individual's fitness.

  2. Social entrepreneurship and social networks

    OpenAIRE

    Dufays, Frédéric

    2013-01-01

    In this presentation, we argue that the sociology of social networks may provide interesting insights with regard to the emergence of social entrepreneurship both at micro and macro levels. There have already been several calls for research on social networks in the context of social entrepreneurship (Certo & Miller 2008; Gedajlovic, et al. 2013; Haugh 2007; Mair & Marti 2006; Short, et al. 2009). These calls often address the differences in structure and effects of social networks in a socia...

  3. Modeling Social Capital as Dynamic Networks to Promote Access to Oral Healthcare.

    Science.gov (United States)

    Wang, Hua; Northridge, Mary E; Kunzel, Carol; Zhang, Qiuyi; Kum, Susan S; Gilbert, Jessica L; Jin, Zhu; Metcalf, Sara S

    2016-01-01

    Social capital, as comprised of human connections in social networks and their associated benefits, is closely related to the health of individuals, communities, and societies at large. For disadvantaged population groups such as older adults and racial/ethnic minorities, social capital may play a particularly critical role in mitigating the negative effects and reinforcing the positive effects on health. In this project, we model social capital as both cause and effect by simulating dynamic networks. Informed in part by a community-based health promotion program, an agent-based model is contextualized in a GIS environment to explore the complexity of social disparities in oral and general health as experienced at the individual, interpersonal, and community scales. This study provides the foundation for future work investigating how health and healthcare accessibility may be influenced by social networks.

  4. A model of spreading of sudden events on social networks

    Science.gov (United States)

    Wu, Jiao; Zheng, Muhua; Zhang, Zi-Ke; Wang, Wei; Gu, Changgui; Liu, Zonghua

    2018-03-01

    Information spreading has been studied for decades, but its underlying mechanism is still under debate, especially for those ones spreading extremely fast through the Internet. By focusing on the information spreading data of six typical events on Sina Weibo, we surprisingly find that the spreading of modern information shows some new features, i.e., either extremely fast or slow, depending on the individual events. To understand its mechanism, we present a susceptible-accepted-recovered model with both information sensitivity and social reinforcement. Numerical simulations show that the model can reproduce the main spreading patterns of the six typical events. By this model, we further reveal that the spreading can be speeded up by increasing either the strength of information sensitivity or social reinforcement. Depending on the transmission probability and information sensitivity, the final accepted size can change from continuous to discontinuous transition when the strength of the social reinforcement is large. Moreover, an edge-based compartmental theory is presented to explain the numerical results. These findings may be of significance on the control of information spreading in modern society.

  5. Online social support networks.

    Science.gov (United States)

    Mehta, Neil; Atreja, Ashish

    2015-04-01

    Peer support groups have a long history and have been shown to improve health outcomes. With the increasing familiarity with online social networks like Facebook and ubiquitous access to the Internet, online social support networks are becoming popular. While studies have shown the benefit of these networks in providing emotional support or meeting informational needs, robust data on improving outcomes such as a decrease in health services utilization or reduction in adverse outcomes is lacking. These networks also pose unique challenges in the areas of patient privacy, funding models, quality of content, and research agendas. Addressing these concerns while creating patient-centred, patient-powered online support networks will help leverage these platforms to complement traditional healthcare delivery models in the current environment of value-based care.

  6. Getting acquainted through social networking sites: testing a model of online uncertainty reduction and social attraction

    NARCIS (Netherlands)

    Antheunis, M.L.; Valkenburg, P.M.; Peter, J.

    2010-01-01

    The first aim of this study was to examine which uncertainty reduction strategies members of social network sites used to gain information about a person who they had recently met online. The second aim was to investigate whether and how these uncertainty reduction strategies resulted in social

  7. Getting acquainted through social networking sites: Testing a model of online uncertainty reduction and social attraction

    NARCIS (Netherlands)

    Antheunis, M.L.; Valkenburg, P.M.; Peter, J.

    2008-01-01

    The first aim of this study was to examine which uncertainty reduction strategies members of social networking sites used to gain information about a person who they had recently met online. The second aim was to investigate whether and how these uncertainty reduction strategies resulted in social

  8. Analysis of Social Network Dynamics with Models from the Theory of Complex Adaptive Systems

    OpenAIRE

    Lymperopoulos , Ilias; Lekakos , George

    2013-01-01

    Part 4: Protocols, Regulation and Social Networking; International audience; The understanding and modeling of social dynamics in a complex and unpredictable world, emerges as a research target of particular importance. Success in this direction can yield valuable knowledge as to how social phenomena form and evolve in varying socioeconomic contexts comprising economic crises, societal disasters, cultural differences and security threats among others. The study of social dynamics occurring in...

  9. An economic model of friendship and enmity for measuring social balance in networks

    Science.gov (United States)

    Lee, Kyu-Min; Shin, Euncheol; You, Seungil

    2017-12-01

    We propose a dynamic economic model of networks where agents can be friends or enemies with one another. This is a decentralized relationship model in that agents decide whether to change their relationships so as to minimize their imbalanced triads. In this model, there is a single parameter, which we call social temperature, that captures the degree to which agents care about social balance in their relationships. We show that the global structure of relationship configuration converges to a unique stationary distribution. Using this stationary distribution, we characterize the maximum likelihood estimator of the social temperature parameter. Since the estimator is computationally challenging to calculate from real social network datasets, we provide a simple simulation algorithm and verify its performance with real social network datasets.

  10. An Agent Model for a Human’s Social Support Network Tie Preference During Depression

    NARCIS (Netherlands)

    Aziz, A.A.; Klein, M.C.A.; Treur, J.; Baeza-Yates, R.; Lang, J.; Mitra, S.; Parsons, S.; Pasi, G.

    2009-01-01

    Seeking support from their environment is important for people suffering from a depression. People usually have different social networks to which they are attached with different ties. In this paper, a computational model is presented that describes the selection of network members for seeking

  11. Visualization of Social Networks

    NARCIS (Netherlands)

    Boertjes, E.M.; Kotterink, B.; Jager, E.J.

    2011-01-01

    Current visualizations of social networks are mostly some form of node-link diagram. Depending on the type of social network, this can be some treevisualization with a strict hierarchical structure or a more generic network visualization.

  12. Modeling Temporal Variation in Social Network: An Evolutionary Web Graph Approach

    Science.gov (United States)

    Mitra, Susanta; Bagchi, Aditya

    A social network is a social structure between actors (individuals, organization or other social entities) and indicates the ways in which they are connected through various social relationships like friendships, kinships, professional, academic etc. Usually, a social network represents a social community, like a club and its members or a city and its citizens etc. or a research group communicating over Internet. In seventies Leinhardt [1] first proposed the idea of representing a social community by a digraph. Later, this idea became popular among other research workers like, network designers, web-service application developers and e-learning modelers. It gave rise to a rapid proliferation of research work in the area of social network analysis. Some of the notable structural properties of a social network are connectedness between actors, reachability between a source and a target actor, reciprocity or pair-wise connection between actors with bi-directional links, centrality of actors or the important actors having high degree or more connections and finally the division of actors into sub-structures or cliques or strongly-connected components. The cycles present in a social network may even be nested [2, 3]. The formal definition of these structural properties will be provided in Sect. 8.2.1. The division of actors into cliques or sub-groups can be a very important factor for understanding a social structure, particularly the degree of cohesiveness in a community. The number, size, and connections among the sub-groups in a network are useful in understanding how the network, as a whole, is likely to behave.

  13. How Crime Spreads Through Imitation in Social Networks: A Simulation Model

    Science.gov (United States)

    Punzo, Valentina

    In this chapter an agent-based model for investigating how crime spreads through social networks is presented. Some theoretical issues related to the sociological explanation of crime are tested through simulation. The agent-based simulation allows us to investigate the relative impact of some mechanisms of social influence on crime, within a set of controlled simulated experiments.

  14. Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis

    Science.gov (United States)

    Dean, Danielle O.; Bauer, Daniel J.; Prinstein, Mitchell J.

    2018-01-01

    A social network perspective can bring important insight into the processes that shape human behavior. Longitudinal social network data, measuring relations between individuals over time, has become increasingly common—as have the methods available to analyze such data. A friendship duration model utilizing discrete-time multilevel survival analysis with a multiple membership random effect structure is developed and applied here to study the processes leading to undirected friendship dissolution within a larger social network. While the modeling framework is introduced in terms of understanding friendship dissolution, it can be used to understand microlevel dynamics of a social network more generally. These models can be fit with standard generalized linear mixed-model software, after transforming the data to a pair-period data set. An empirical example highlights how the model can be applied to understand the processes leading to friendship dissolution between high school students, and a simulation study is used to test the use of the modeling framework under representative conditions that would be found in social network data. Advantages of the modeling framework are highlighted, and potential limitations and future directions are discussed. PMID:28463022

  15. Modeling cascading failures with the crisis of trust in social networks

    Science.gov (United States)

    Yi, Chengqi; Bao, Yuanyuan; Jiang, Jingchi; Xue, Yibo

    2015-10-01

    In social networks, some friends often post or disseminate malicious information, such as advertising messages, informal overseas purchasing messages, illegal messages, or rumors. Too much malicious information may cause a feeling of intense annoyance. When the feeling exceeds a certain threshold, it will lead social network users to distrust these friends, which we call the crisis of trust. The crisis of trust in social networks has already become a universal concern and an urgent unsolved problem. As a result of the crisis of trust, users will cut off their relationships with some of their untrustworthy friends. Once a few of these relationships are made unavailable, it is likely that other friends will decline trust, and a large portion of the social network will be influenced. The phenomenon in which the unavailability of a few relationships will trigger the failure of successive relationships is known as cascading failure dynamics. To our best knowledge, no one has formally proposed cascading failures dynamics with the crisis of trust in social networks. In this paper, we address this potential issue, quantify the trust between two users based on user similarity, and model the minimum tolerance with a nonlinear equation. Furthermore, we construct the processes of cascading failures dynamics by considering the unique features of social networks. Based on real social network datasets (Sina Weibo, Facebook and Twitter), we adopt two attack strategies (the highest trust attack (HT) and the lowest trust attack (LT)) to evaluate the proposed dynamics and to further analyze the changes of the topology, connectivity, cascading time and cascade effect under the above attacks. We numerically find that the sparse and inhomogeneous network structure in our cascading model can better improve the robustness of social networks than the dense and homogeneous structure. However, the network structure that seems like ripples is more vulnerable than the other two network

  16. Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

    Science.gov (United States)

    Ward, Jonathan A.; Grindrod, Peter

    2014-07-01

    Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance

  17. Tolerance-based interaction: a new model targeting opinion formation and diffusion in social networks

    Directory of Open Access Journals (Sweden)

    Alexandru Topirceanu

    2016-01-01

    Full Text Available One of the main motivations behind social network analysis is the quest for understanding opinion formation and diffusion. Previous models have limitations, as they typically assume opinion interaction mechanisms based on thresholds which are either fixed or evolve according to a random process that is external to the social agent. Indeed, our empirical analysis on large real-world datasets such as Twitter, Meme Tracker, and Yelp, uncovers previously unaccounted for dynamic phenomena at population-level, namely the existence of distinct opinion formation phases and social balancing. We also reveal that a phase transition from an erratic behavior to social balancing can be triggered by network topology and by the ratio of opinion sources. Consequently, in order to build a model that properly accounts for these phenomena, we propose a new (individual-level opinion interaction model based on tolerance. As opposed to the existing opinion interaction models, the new tolerance model assumes that individual’s inner willingness to accept new opinions evolves over time according to basic human traits. Finally, by employing discrete event simulation on diverse social network topologies, we validate our opinion interaction model and show that, although the network size and opinion source ratio are important, the phase transition to social balancing is mainly fostered by the democratic structure of the small-world topology.

  18. An epidemic model of rumor diffusion in online social networks

    Science.gov (United States)

    Cheng, Jun-Jun; Liu, Yun; Shen, Bo; Yuan, Wei-Guo

    2013-01-01

    So far, in some standard rumor spreading models, the transition probability from ignorants to spreaders is always treated as a constant. However, from a practical perspective, the case that individual whether or not be infected by the neighbor spreader greatly depends on the trustiness of ties between them. In order to solve this problem, we introduce a stochastic epidemic model of the rumor diffusion, in which the infectious probability is defined as a function of the strength of ties. Moreover, we investigate numerically the behavior of the model on a real scale-free social site with the exponent γ = 2.2. We verify that the strength of ties plays a critical role in the rumor diffusion process. Specially, selecting weak ties preferentially cannot make rumor spread faster and wider, but the efficiency of diffusion will be greatly affected after removing them. Another significant finding is that the maximum number of spreaders max( S) is very sensitive to the immune probability μ and the decay probability v. We show that a smaller μ or v leads to a larger spreading of the rumor, and their relationships can be described as the function ln(max( S)) = Av + B, in which the intercept B and the slope A can be fitted perfectly as power-law functions of μ. Our findings may offer some useful insights, helping guide the application in practice and reduce the damage brought by the rumor.

  19. Customer social network affects marketing strategy: A simulation analysis based on competitive diffusion model

    Science.gov (United States)

    Hou, Rui; Wu, Jiawen; Du, Helen S.

    2017-03-01

    To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.

  20. Social network data analytics

    CERN Document Server

    Aggarwal, Charu C

    2011-01-01

    Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Pr

  1. Enterprise Social Networks

    DEFF Research Database (Denmark)

    Winkler, Till J.; Trier, Matthias

    2017-01-01

    Enterprise Social Networks (ESNs), d. h. Informationssysteme, die die Vernetzung von Mitarbeitern in Unternehmen fördern sollen, sind in verschiedenen Varianten und unter verschiedenen Bezeichnungen (etwa Enterprise Social Media, Corporate Social Software, Social Business oder Enterprise 2...

  2. The social networking application success model : An empirical study of Facebook and Twitter

    NARCIS (Netherlands)

    Ou, Carol; Davison, R.M.; Huang, Q.

    2016-01-01

    Social networking applications (SNAs) are among the fastest growing web applications of recent years. In this paper, we propose a causal model to assess the success of SNAs, grounded on DeLone and McLean’s updated information systems (IS) success model. In addition to their original three dimensions

  3. Modeling the effect of social networks on adoption of multifunctional agriculture.

    Science.gov (United States)

    Manson, Steven M; Jordan, Nicholas R; Nelson, Kristen C; Brummel, Rachel F

    2016-01-01

    Rotational grazing (RG) has attracted much attention as a cornerstone of multifunctional agriculture (MFA) in animal systems, potentially capable of producing a range of goods and services of value to diverse stakeholders in agricultural landscapes and rural communities, as well as broader societal benefits. Despite these benefits, global adoption of MFA has been uneven, with some places seeing active participation, while others have seen limited growth. Recent conceptual models of MFA emphasize the potential for bottom-up processes and linkages among social and environmental systems to promote multifunctionality. Social networks are critical to these explanations but how and why these networks matter is unclear. We investigated fifty-three farms in three states in the United States (New York, Wisconsin, Pennsylvania) and developed a stylized model of social networks and systemic change in the dairy farming system. We found that social networks are important to RG adoption but their impact is contingent on social and spatial factors. Effects of networks on farmer decision making differ according to whether they comprise weak-tie relationships, which bridge across disparate people and organizations, or strong-tie relationships, which are shared by groups in which members are well known to one another. RG adoption is also dependent on features of the social landscape including the number of dairy households, the probability of neighboring farmers sharing strong ties, and the role of space in how networks are formed. The model replicates features of real-world adoption of RG practices in the Eastern US and illustrates pathways toward greater multifunctionality in the dairy landscape. Such models are likely to be of heuristic value in network-focused strategies for agricultural development.

  4. Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting

    Science.gov (United States)

    Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.

    2016-01-01

    Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048

  5. Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

    Science.gov (United States)

    Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

    2017-02-01

    Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

  6. HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP) MODEL

    OpenAIRE

    Chun Meng Tang; Miang Hong Ngerng

    2015-01-01

    Social networking sites are popular among university students, and students today are indeed spoiled for choice. New emerging social networking sites sprout up amid popular sites, while some existing ones die out. Given the choice of so many social networking sites, how do students decide which one they will sign up for and stay on as an active user? The answer to this question is of interest to social networking site designers and marketers. The market of social networking sites is highly co...

  7. Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster Random Effects Models.

    Science.gov (United States)

    Krivitsky, Pavel N; Handcock, Mark S; Raftery, Adrian E; Hoff, Peter D

    2009-07-01

    Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesian estimation method for it. The model is applicable to both binary and non-binary network data. We illustrate the model using two real datasets. We also apply it to two simulated network datasets with the same, highly skewed, degree distribution, but very different network behavior: one unstructured and the other with transitivity and clustering. Models based on degree distributions, such as scale-free, preferential attachment and power-law models, cannot distinguish between these very different situations, but our model does.

  8. Disrupting Cocaine Trafficking Networks: Interdicting a Combined Social-Functional Network Model

    Science.gov (United States)

    2016-03-01

    BENEFITS OF STUDY ....................................14  E.  SOCIAL-FUNCTIONAL NETWORK DESCRIPTION .....................16  1.  A Representative...data to maintain appropriate classification levels) of cocaine produced each month by the Colombian sources to the U.S. homeland, netting the...Tactical interdiction-centric operational approaches have improved over the years due to previous studies and research, but these approaches rely upon one

  9. Accelerating a Network Model of Care: Taking a Social Innovation to Scale

    Directory of Open Access Journals (Sweden)

    Kerry Byrne

    2012-07-01

    Full Text Available Government-funded systems of health and social care are facing enormous fiscal and human-resource challenges. The space for innovation in care is wide open and new disruptive patterns are emerging. These include self-management and personal budgets, participatory and integrated care, supported decision making and a renewed focus on prevention. Taking these disruptive patterns to scale can be accelerated by a technologically enabled shift to a network model of care to co-create the best outcomes for individuals, family caregivers, and health and social care organizations. The connections, relationships, and activities within an individual’s personal network lay the foundation for care that health and social care systems/policy must simultaneously support and draw on for positive outcomes. Practical tools, adequate information, and tangible resources are required to coordinate and sustain care. Tyze Personal Networks is a social venture that uses technology to engage and inform the individual, their personal networks, and their care providers to co-create the best outcomes. In this article, we demonstrate how Tyze contributes to a shift to a network model of care by strengthening our networks and enhancing partnerships between care providers, individuals, and family and friends.

  10. Modeling Social Influences in a Knowledge Management Network

    Science.gov (United States)

    Franco, Giacomo; Maresca, Paolo; Nota, Giancarlo

    2010-01-01

    The issue of knowledge management in a distributed network is receiving increasing attention from both scientific and industrial organizations. Research efforts in this field are motivated by the awareness that knowledge is more and more perceived as a primary economic resource and that, in the context of organization of organizations, the…

  11. Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

    Science.gov (United States)

    Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

    The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

  12. Social adaptation in multi-agent model of linguistic categorization is affected by network information flow.

    Science.gov (United States)

    Zubek, Julian; Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz

    2017-01-01

    This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems.

  13. Dynamic vs. static social networks in models of parasite transmission: predicting Cryptosporidium spread in wild lemurs.

    Science.gov (United States)

    Springer, Andrea; Kappeler, Peter M; Nunn, Charles L

    2017-05-01

    Social networks provide an established tool to implement heterogeneous contact structures in epidemiological models. Dynamic temporal changes in contact structure and ranging behaviour of wildlife may impact disease dynamics. A consensus has yet to emerge, however, concerning the conditions in which network dynamics impact model outcomes, as compared to static approximations that average contact rates over longer time periods. Furthermore, as many pathogens can be transmitted both environmentally and via close contact, it is important to investigate the relative influence of both transmission routes in real-world populations. Here, we use empirically derived networks from a population of wild primates, Verreaux's sifakas (Propithecus verreauxi), and simulated networks to investigate pathogen spread in dynamic vs. static social networks. First, we constructed a susceptible-exposed-infected-recovered model of Cryptosporidium spread in wild Verreaux's sifakas. We incorporated social and environmental transmission routes and parameterized the model for two different climatic seasons. Second, we used simulated networks and greater variation in epidemiological parameters to investigate the conditions in which dynamic networks produce larger outbreak sizes than static networks. We found that average outbreak size of Cryptosporidium infections in sifakas was larger when the disease was introduced in the dry season than in the wet season, driven by an increase in home range overlap towards the end of the dry season. Regardless of season, dynamic networks always produced larger average outbreak sizes than static networks. Larger outbreaks in dynamic models based on simulated networks occurred especially when the probability of transmission and recovery were low. Variation in tie strength in the dynamic networks also had a major impact on outbreak size, while network modularity had a weaker influence than epidemiological parameters that determine transmission and recovery

  14. Modelling of information diffusion on social networks with applications to WeChat

    Science.gov (United States)

    Liu, Liang; Qu, Bo; Chen, Bin; Hanjalic, Alan; Wang, Huijuan

    2018-04-01

    Traces of user activities recorded in online social networks open new possibilities to systematically understand the information diffusion process on social networks. From the online social network WeChat, we collected a large number of information cascade trees, each of which tells the spreading trajectory of a message/information such as which user creates the information and which users view or forward the information shared by which neighbours. In this work, we propose two heterogeneous non-linear models, one for the topologies of the information cascade trees and the other for the stochastic process of information diffusion on a social network. Both models are validated by the WeChat data in reproducing and explaining key features of cascade trees. Specifically, we apply the Random Recursive Tree (RRT) to model the growth of cascade trees. The RRT model could capture key features, i.e. the average path length and degree variance of a cascade tree in relation to the number of nodes (size) of the tree. Its single identified parameter quantifies the relative depth or broadness of the cascade trees and indicates that information propagates via a star-like broadcasting or viral-like hop by hop spreading. The RRT model explains the appearance of hubs, thus a possibly smaller average path length as the cascade size increases, as observed in WeChat. We further propose the stochastic Susceptible View Forward Removed (SVFR) model to depict the dynamic user behaviour including creating, viewing, forwarding and ignoring a message on a given social network. Beside the average path length and degree variance of the cascade trees in relation to their sizes, the SVFR model could further explain the power-law cascade size distribution in WeChat and unravel that a user with a large number of friends may actually have a smaller probability to read a message (s)he receives due to limited attention.

  15. Impact of Social Network and Business Model on Innovation Diffusion of Electric Vehicles in China

    Directory of Open Access Journals (Sweden)

    D. Y. Kong

    2014-01-01

    Full Text Available The diffusion of electric vehicles (EVs involves not only the technological development but also the construction of complex social networks. This paper uses the theory of network control to analyze the influence of network forms on EV diffusion in China, especially focusing on the building of EV business models (BMs and the resulting effects and control on the diffusion of EVs. The Bass model is adopted to forecast the diffusion process of EVs and genetic algorithm is used to estimate the parameters based on the diffusion data of Hybrid Electric Vehicle (HEV in the United States and Japan. Two different social network forms and BMs are selected, that is, battery leasing model and vehicle purchasing model, to analyze how different network forms may influence the innovation coefficient and imitation coefficient in the Bass model, which will in turn result in different diffusion results. Thereby, we can find the appropriate network forms and BMs for EVs which is suitable to the local market conditions.

  16. Agent-Based Modeling of China's Rural-Urban Migration and Social Network Structure.

    Science.gov (United States)

    Fu, Zhaohao; Hao, Lingxin

    2018-01-15

    We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k -core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

  17. Agent-based modeling of China's rural-urban migration and social network structure

    Science.gov (United States)

    Fu, Zhaohao; Hao, Lingxin

    2018-01-01

    We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k-core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

  18. Active influence in dynamical models of structural balance in social networks

    Science.gov (United States)

    Summers, Tyler H.; Shames, Iman

    2013-07-01

    We consider a nonlinear dynamical system on a signed graph, which can be interpreted as a mathematical model of social networks in which the links can have both positive and negative connotations. In accordance with a concept from social psychology called structural balance, the negative links play a key role in both the structure and dynamics of the network. Recent research has shown that in a nonlinear dynamical system modeling the time evolution of “friendliness levels” in the network, two opposing factions emerge from almost any initial condition. Here we study active external influence in this dynamical model and show that any agent in the network can achieve any desired structurally balanced state from any initial condition by perturbing its own local friendliness levels. Based on this result, we also introduce a new network centrality measure for signed networks. The results are illustrated in an international-relations network using United Nations voting record data from 1946 to 2008 to estimate friendliness levels amongst various countries.

  19. Network-oriented modeling addressing complexity of cognitive, affective and social interactions

    CERN Document Server

    Treur, Jan

    2016-01-01

    This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including ...

  20. Individuals' spatial social network choice: model-based analysis of leisure-contact selection

    NARCIS (Netherlands)

    Kowald, M.; Arentze, Theo A.; Axhausen, K.W.

    2015-01-01

    Leisure travel holds an important share of the overall amount of travel. However, efforts in transport planning to model and explain leisure travel have been rather limited for a long time. Only recently, a subcommunity of researchers began to use the methods of social network analysis. Existing

  1. In-House Communication Support System Based on the Information Propagation Model Utilizes Social Network

    Science.gov (United States)

    Takeuchi, Susumu; Teranishi, Yuuichi; Harumoto, Kaname; Shimojo, Shinji

    Almost all companies are now utilizing computer networks to support speedier and more effective in-house information-sharing and communication. However, existing systems are designed to support communications only within the same department. Therefore, in our research, we propose an in-house communication support system which is based on the “Information Propagation Model (IPM).” The IPM is proposed to realize word-of-mouth communication in a social network, and to support information-sharing on the network. By applying the system in a real company, we found that information could be exchanged between different and unrelated departments, and such exchanges of information could help to build new relationships between the users who are apart on the social network.

  2. A context-sensitive trust model for online social networking

    CSIR Research Space (South Africa)

    Danny, MN

    2016-11-01

    Full Text Available of privacy attacks. In the quest to address this problem, this paper proposes a context-sensitive trust model. The proposed trust model was designed using fuzzy logic theory and implemented using MATLAB. Contrary to existing trust models, the context...

  3. Professional social networking.

    Science.gov (United States)

    Rowley, Robert D

    2014-12-01

    We review the current state of social communication between healthcare professionals, the role of consumer social networking, and some emerging technologies to address the gaps. In particular, the review covers (1) the current state of loose social networking for continuing medical education (CME) and other broadcast information dissemination; (2) social networking for business promotion; (3) social networking for peer collaboration, including simple communication as well as more robust data-centered collaboration around patient care; and (4) engaging patients on social platforms, including integrating consumer-originated data into the mix of healthcare data. We will see how, as the nature of healthcare delivery moves from the institution-centric way of tradition to a more social and networked ambulatory pattern that we see emerging today, the nature of health IT has also moved from enterprise-centric systems to more socially networked, cloud-based options.

  4. Social network usage, shame, guilt and pride among high school students: Model testing

    OpenAIRE

    Doğan, Uğur; Çelik, Eyüp; Karakaş, Yahya

    2016-01-01

    This study was aimed at testing a model which applies structural equation modeling (SEM) to explain social networking sites (SNS) usage. Performing SEM with a sample of 500 high school students (40% male, 60% female), the model examined the relationships among shame, guilt and pride on SNS, such Facebook and Twitter. It was hypothesized that SNS usage was predicted directly by shame and indirectly by pride and guilt. The SEM showed that shame affected SNS usage directly and positively, while ...

  5. An information search model for online social Networks - MOBIRSE

    OpenAIRE

    Miguel Angel Niño Zambrano; Iván Darío Cerón Moreno; Jhon Alberto Astaiza Perafán; Gustavo Adolfo Ramírez

    2015-01-01

    En los últimos años las Redes Sociales Online (RSO) han venido cobrando gran importancia entre los usuarios de Internet, puesto que son sitios donde se puede conocer personas, publicar y compartir contenidos de una manera fácil y gratuita. Esto ha provocado que el volumen de información contenida en estos sitios web crezca de manera exponencial. Por lo tanto, la búsqueda web se convierte en una herramienta importante para que los usuarios puedan encontrar fácilmente la información relevante p...

  6. Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

    Science.gov (United States)

    Baker-Doyle, Kira J.

    2015-01-01

    Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

  7. Next Generation Social Networks

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Skouby, Knud Erik

    2008-01-01

    different online networks for communities of people who share interests or individuals who presents themselves through user produced content is what makes up the social networking of today. The purpose of this paper is to discuss perceived user requirements to the next generation social networks. The paper...

  8. Risk aversion and social networks

    NARCIS (Netherlands)

    Kovarik, J.; van der Leij, M.J.

    2011-01-01

    Agents involved in the formation of a social or economic network typically face uncertainty about the benefits of creating a link. However, the interplay of such uncertainty and risk attitudes has been neglected in the network formation literature. We propose a dynamic network formation model that

  9. Risk aversion and social networks

    NARCIS (Netherlands)

    Kovářík, J.; van der Leij, M.J.

    2012-01-01

    Agents involved in the formation of a social or economic network typically face uncertainty about the benefits of creating a link. However, the interplay of such uncertainty and risk attitudes has been neglected in the network formation literature. We propose a dynamic network formation model that

  10. A Privacy Preservation Model for Health-Related Social Networking Sites

    Science.gov (United States)

    2015-01-01

    The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS. PMID:26155953

  11. A Privacy Preservation Model for Health-Related Social Networking Sites.

    Science.gov (United States)

    Li, Jingquan

    2015-07-08

    The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS.

  12. A novel game theoretic approach for modeling competitive information diffusion in social networks with heterogeneous nodes

    Science.gov (United States)

    Agha Mohammad Ali Kermani, Mehrdad; Fatemi Ardestani, Seyed Farshad; Aliahmadi, Alireza; Barzinpour, Farnaz

    2017-01-01

    Influence maximization deals with identification of the most influential nodes in a social network given an influence model. In this paper, a game theoretic framework is developed that models a competitive influence maximization problem. A novel competitive influence model is additionally proposed that incorporates user heterogeneity, message content, and network structure. The proposed game-theoretic model is solved using Nash Equilibrium in a real-world dataset. It is shown that none of the well-known strategies are stable and at least one player has the incentive to deviate from the proposed strategy. Moreover, violation of Nash equilibrium strategy by each player leads to their reduced payoff. Contrary to previous works, our results demonstrate that graph topology, as well as the nodes' sociability and initial tendency measures have an effect on the determination of the influential node in the network.

  13. Detecting Rumors Through Modeling Information Propagation Networks in a Social Media Environment.

    Science.gov (United States)

    Liu, Yang; Xu, Songhua; Tourassi, Georgia

    2015-01-01

    In the midst of today's pervasive influence of social media content and activities, information credibility has increasingly become a major issue. Accordingly, identifying false information, e.g. rumors circulated in social media environments, attracts expanding research attention and growing interests. Many previous studies have exploited user-independent features for rumor detection. These prior investigations uniformly treat all users relevant to the propagation of a social media message as instances of a generic entity. Such a modeling approach usually adopts a homogeneous network to represent all users, the practice of which ignores the variety across an entire user population in a social media environment. Recognizing this limitation of modeling methodologies, this study explores user-specific features in a social media environment for rumor detection. The new approach hypothesizes that whether a user tends to spread a rumor is dependent upon specific attributes of the user in addition to content characteristics of the message itself. Under this hypothesis, information propagation patterns of rumors versus those of credible messages in a social media environment are systematically differentiable. To explore and exploit this hypothesis, we develop a new information propagation model based on a heterogeneous user representation for rumor recognition. The new approach is capable of differentiating rumors from credible messages through observing distinctions in their respective propagation patterns in social media. Experimental results show that the new information propagation model based on heterogeneous user representation can effectively distinguish rumors from credible social media content.

  14. Social cognitive radio networks

    CERN Document Server

    Chen, Xu

    2015-01-01

    This brief presents research results on social cognitive radio networks, a transformational and innovative networking paradigm that promotes the nexus between social interactions and cognitive radio networks. Along with a review of the research literature, the text examines the key motivation and challenges of social cognitive radio network design. Three socially inspired distributed spectrum sharing mechanisms are introduced: adaptive channel recommendation mechanism, imitation-based social spectrum sharing mechanism, and evolutionarily stable spectrum access mechanism. The brief concludes with a discussion of future research directions which ascertains that exploiting social interactions for distributed spectrum sharing will advance the state-of-the-art of cognitive radio network design, spur a new line of thinking for future wireless networks, and enable novel wireless service and applications.

  15. The data-driven null models for information dissemination tree in social networks

    Science.gov (United States)

    Zhang, Zhiwei; Wang, Zhenyu

    2017-10-01

    For the purpose of detecting relatedness and co-occurrence between users, as well as the distribution features of nodes in spreading path of a social network, this paper explores topological characteristics of information dissemination trees (IDT) that can be employed indirectly to probe the information dissemination laws within social networks. Hence, three different null models of IDT are presented in this article, including the statistical-constrained 0-order IDT null model, the random-rewire-broken-edge 0-order IDT null model and the random-rewire-broken-edge 2-order IDT null model. These null models firstly generate the corresponding randomized copy of an actual IDT; then the extended significance profile, which is developed by adding the cascade ratio of information dissemination path, is exploited not only to evaluate degree correlation of two nodes associated with an edge, but also to assess the cascade ratio of different length of information dissemination paths. The experimental correspondences of the empirical analysis for several SinaWeibo IDTs and Twitter IDTs indicate that the IDT null models presented in this paper perform well in terms of degree correlation of nodes and dissemination path cascade ratio, which can be better to reveal the features of information dissemination and to fit the situation of real social networks.

  16. Entropy of dynamical social networks

    Science.gov (United States)

    Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

    2012-02-01

    Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

  17. Reliability and Efficiency of Generalized Rumor Spreading Model on Complex Social Networks

    International Nuclear Information System (INIS)

    Naimi, Yaghoob; Naimi, Mohammad

    2013-01-01

    We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks. Despite pervious rumor models that both the spreader-spreader (SS) and the spreader-stifler (SR) interactions have the same rate α, we define α (1) and α (2) for SS and SR interactions, respectively. The effect of variation of α (1) and α (2) on the final density of stiflers is investigated. Furthermore, the influence of the topological structure of the network in rumor spreading is studied by analyzing the behavior of several global parameters such as reliability and efficiency. Our results show that while networks with homogeneous connectivity patterns reach a higher reliability, scale-free topologies need a less time to reach a steady state with respect the rumor. (interdisciplinary physics and related areas of science and technology)

  18. Privacy in Social Networks

    CERN Document Server

    Zheleva, Elena

    2012-01-01

    This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third parties. Our goal is to approach such concerns from a computer-science perspective, and building upon existing work on privacy, security, statistical modeling and databases to provide an overview of the technical and algorithmic issues related to privacy in OSNs. We start our survey by introducing a simple OSN data model and describe common statistical-inference techniques that can be used to infer potentially sensitive inf

  19. A Game Theoretic Approach for Modeling Privacy Settings of an Online Social Network

    Directory of Open Access Journals (Sweden)

    Jundong Chen

    2014-05-01

    Full Text Available Users of online social networks often adjust their privacy settings to control how much information on their profiles is accessible to other users of the networks. While a variety of factors have been shown to affect the privacy strategies of these users, very little work has been done in analyzing how these factors influence each other and collectively contribute towards the users’ privacy strategies. In this paper, we analyze the influence of attribute importance, benefit, risk and network topology on the users’ attribute disclosure behavior by introducing a weighted evolutionary game model. Results show that: irrespective of risk, users aremore likely to reveal theirmost important attributes than their least important attributes; when the users’ range of influence is increased, the risk factor plays a smaller role in attribute disclosure; the network topology exhibits a considerable effect on the privacy in an environment with risk.

  20. A Mechanistic Model of Human Recall of Social Network Structure and Relationship Affect.

    Science.gov (United States)

    Omodei, Elisa; Brashears, Matthew E; Arenas, Alex

    2017-12-07

    The social brain hypothesis argues that the need to deal with social challenges was key to our evolution of high intelligence. Research with non-human primates as well as experimental and fMRI studies in humans produce results consistent with this claim, leading to an estimate that human primary groups should consist of roughly 150 individuals. Gaps between this prediction and empirical observations can be partially accounted for using "compression heuristics", or schemata that simplify the encoding and recall of social information. However, little is known about the specific algorithmic processes used by humans to store and recall social information. We describe a mechanistic model of human network recall and demonstrate its sufficiency for capturing human recall behavior observed in experimental contexts. We find that human recall is predicated on accurate recall of a small number of high degree network nodes and the application of heuristics for both structural and affective information. This provides new insight into human memory, social network evolution, and demonstrates a novel approach to uncovering human cognitive operations.

  1. A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

    Science.gov (United States)

    Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

    2015-01-01

    We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey. PMID:25859056

  2. Social insect colony as a biological regulatory system: modelling information flow in dominance networks.

    Science.gov (United States)

    Nandi, Anjan K; Sumana, Annagiri; Bhattacharya, Kunal

    2014-12-06

    Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  3. Multilayer Social Networks

    DEFF Research Database (Denmark)

    Dickison, Mark; Magnani, Matteo; Rossi, Luca

    social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various...

  4. Social traits, social networks and evolutionary biology.

    Science.gov (United States)

    Fisher, D N; McAdam, A G

    2017-12-01

    The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals' network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group-level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic

  5. Social inheritance can explain the structure of animal social networks

    Science.gov (United States)

    Ilany, Amiyaal; Akçay, Erol

    2016-01-01

    The social network structure of animal populations has major implications for survival, reproductive success, sexual selection and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output with data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance. PMID:27352101

  6. Social Networks and Health.

    Science.gov (United States)

    Perdiaris, Christos; Chardalias, Konstantinos; Magita, Andrianna; Mechili, Aggelos E; Diomidous, Marianna

    2015-01-01

    Nowadays the social networks have been developed into an advanced communications tool, which is important for all people to contact each other. These specific networks do offer lots of options as well as plenty of advantages and disadvantages. The social websites are many in number and titles, such as the facebook, the twitter, the bandoo etc. One of the most important function-mechanisms for the social network websites, are the marketing tools. The future goal is suggested to be the evolution of these programs. The development of these applications, which is going to lead into a new era for the social digital communication between the internet users, all around the globe.

  7. Attachment and social networks.

    Science.gov (United States)

    Gillath, Omri; C Karantzas, Gery; Lee, Juwon

    2018-02-21

    The current review covers two lines of research linking attachment and social networks. One focuses on attachment networks (the people who fulfill one's attachment needs), examining composition and age-related differences pertaining to these networks. The other line integrates attachment with social network analysis to investigate how individual differences in adult attachment are associated with the management and characteristics (e.g., density, multiplexity, and centrality) of people's social networks. We show that most people's attachment networks are small and hierarchical, with one figure being the primary attachment figure (often a mother or romantic partner, depending on age). Furthermore, attachment style predicts network characteristics and management, such that insecurity is associated with less closeness, multiplexity, centrality, and poorer management (less maintenance, more dissolution). Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Complexities of social networks: A Physicist's perspective

    OpenAIRE

    Sen, Parongama

    2006-01-01

    The review is a survey of the present status of research in social networks highlighting the topics of small world property, degree distributions, community structure, assortativity, modelling, dynamics and searching in social networks.

  9. Predicting future conflict between team-members with parameter-free models of social networks

    Science.gov (United States)

    Rovira-Asenjo, Núria; Gumí, Tània; Sales-Pardo, Marta; Guimerà, Roger

    2013-06-01

    Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social network structure. We analyze data of conflict appearance and resolution between 86 team members in 16 small teams, all working in a real project for nine consecutive months. We find that group-based models of complex networks successfully anticipate conflict in small teams whereas micro-based models of structural balance, which have been traditionally used to model conflict, do not.

  10. Using the relational event model (REM) to investigate the temporal dynamics of animal social networks.

    Science.gov (United States)

    Tranmer, Mark; Marcum, Christopher Steven; Morton, F Blake; Croft, Darren P; de Kort, Selvino R

    2015-03-01

    Social dynamics are of fundamental importance in animal societies. Studies on nonhuman animal social systems often aggregate social interaction event data into a single network within a particular time frame. Analysis of the resulting network can provide a useful insight into the overall extent of interaction. However, through aggregation, information is lost about the order in which interactions occurred, and hence the sequences of actions over time. Many research hypotheses relate directly to the sequence of actions, such as the recency or rate of action, rather than to their overall volume or presence. Here, we demonstrate how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM). We first outline the REM, explaining why it is different from other models for longitudinal data, and how it can be used to model sequences of events unfolding in a network. We then discuss a case study on the European jackdaw, Corvus monedula , in which temporal patterns of persistence and reciprocity of action are of interest, and present and discuss the results of a REM analysis of these data. One of the strengths of a REM analysis is its ability to take into account different ways in which data are collected. Having explained how to take into account the way in which the data were collected for the jackdaw study, we briefly discuss the application of the model to other studies. We provide details of how the models may be fitted in the R statistical software environment and outline some recent extensions to the REM framework.

  11. Multi-Equilibria Regulation Agent-Based Model of Opinion Dynamics in Social Networks

    Directory of Open Access Journals (Sweden)

    Andreas Koulouris

    2013-01-01

    Full Text Available This article investigates the Multiple Equilibria Regulation (MER model, i.e., an agent-based simulation model, to represent opinion dynamics in social networks. It relies on a small set of micro-prerequisites (intra-individual balance and confidence bound, leading to emergence of (nonstationary macro-outcomes. These outcomes may refer to consensus, polarization or fragmentation of opinions about taxation (e.g., congestion pricing or other policy measures, according to the way communication is structured. In contrast with other models of opinion dynamics, it allows for the impact of both the regulation of intra-personal discrepancy and the interpersonal variability of opinions on social learning and network dynamics. Several simulation experiments are presented to demonstrate, through the MER model, the role of different network structures (complete, star, cellular automata, small-world and random graphs on opinion formation dynamics and the overall evolution of the system. The findings can help to identify specific topological characteristics, such as density, number of neighbourhoods and critical nodes-agents, that affect the stability and system dynamics. This knowledge can be used to better organize the information diffusion and learning in the community, enhance the predictability of outcomes and manage possible conflicts. It is shown that a small-world organization, which depicts more realistic aspects of real-life and virtual social systems, provides increased predictability and stability towards a less fragmented and more manageable grouping of opinions, compared to random networks. Such macro-level organizations may be enhanced with use of web-based technologies to increase the density of communication and public acceptability of policy measures.

  12. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed

    2017-02-07

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals\\'s mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users\\' check-ins and their network of friends, without impairing the model\\'s complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  13. Computational Social Network Analysis

    CERN Document Server

    Hassanien, Aboul-Ella

    2010-01-01

    Presents insight into the social behaviour of animals (including the study of animal tracks and learning by members of the same species). This book provides web-based evidence of social interaction, perceptual learning, information granulation and the behaviour of humans and affinities between web-based social networks

  14. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed; Zhang, Xiangliang

    2017-01-01

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals's mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users' check-ins and their network of friends, without impairing the model's complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  15. FOUNDATION AND DESCRIPTION OF INFORMATIONAL AND PSYCHOLOGICAL DESTRUCTIVE NATURE INFLUENCES DYNAMICS MODEL IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    V. A. Minaev

    2016-10-01

    Full Text Available The article provides a definition of information and psychological technologies and the main channels of information and psychological influences (IPI on social groups. A detailed analysis of the modeling human behavior experience, including the work of Soviet, Russian and foreign scientists is given. It is concluded that mathematical models of information-psychological dynamics influence on the current stage of psychological science development perspective only in relation to mass consciousness. Due to the complexity and poor knowledge of processes occurring in the human psyche and determined his personal peculiarities, the creation of adequate mathematical models of IPI in the individual consciousness is impossible, but for the expert prediction and assessment of the IPI dynamics on a particular member of a social group should use existing proven scientific tests and technique. It has been shown that a significant improvement in the predictability of mathematical models expected in the transition to a dynamic model in the state space. Given verbal and formal description of the model, leading to a form of non-linear differential equation describing the diffusion of innovations. The models take into account of the mass media influence on society, interpersonal information exchange, the effect of forgetting influence. It was emphasized that similar modified mathematical model has given good results in its application to the description of the electoral processes in Russia and spread of ideas of the "Arabian Spring" through social networks.

  16. [Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis].

    Science.gov (United States)

    Díaz Córdova, Diego

    2016-01-01

    The aim of this article is to introduce two methodological strategies that have not often been utilized in the anthropology of food: agent-based models and social networks analysis. In order to illustrate these methods in action, two cases based in materials typical of the anthropology of food are presented. For the first strategy, fieldwork carried out in Quebrada de Humahuaca (province of Jujuy, Argentina) regarding meal recall was used, and for the second, elements of the concept of "domestic consumption strategies" applied by Aguirre were employed. The underlying idea is that, given that eating is recognized as a "total social fact" and, therefore, as a complex phenomenon, the methodological approach must also be characterized by complexity. The greater the number of methods utilized (with the appropriate rigor), the better able we will be to understand the dynamics of feeding in the social environment.

  17. Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

    Science.gov (United States)

    Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

    2013-08-14

    High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary

  18. Social activities and travel demands : a model-based analysis of social-network data

    NARCIS (Netherlands)

    Molin, E.J.E.; Arentze, T.A.; Timmermans, H.J.P.

    2007-01-01

    Social activities are responsible for an important share of trips conducted by individuals. This paper contributes to a rapidly increasing stream of transportation research into individuals' choice of social relations and trips made to maintain their social relations. A method that was used to

  19. Why Do You Adopt Social Networking Sites? Investigating the Driving Factors through Structural Equation Modelling

    Science.gov (United States)

    Jan, Muhammad Tahir

    2017-01-01

    Purpose: The purpose of this paper is to investigate those factors that are associated with the adoption of social networking sites from the perspective of Muslim users residing in Malaysia. Design/methodology/approach: A complete self-administered questionnaire was collected from 223 Muslim users of social networking sites in Malaysia. Both…

  20. A Markov chain model for image ranking system in social networks

    Science.gov (United States)

    Zin, Thi Thi; Tin, Pyke; Toriu, Takashi; Hama, Hiromitsu

    2014-03-01

    In today world, different kinds of networks such as social, technological, business and etc. exist. All of the networks are similar in terms of distributions, continuously growing and expanding in large scale. Among them, many social networks such as Facebook, Twitter, Flickr and many others provides a powerful abstraction of the structure and dynamics of diverse kinds of inter personal connection and interaction. Generally, the social network contents are created and consumed by the influences of all different social navigation paths that lead to the contents. Therefore, identifying important and user relevant refined structures such as visual information or communities become major factors in modern decision making world. Moreover, the traditional method of information ranking systems cannot be successful due to their lack of taking into account the properties of navigation paths driven by social connections. In this paper, we propose a novel image ranking system in social networks by using the social data relational graphs from social media platform jointly with visual data to improve the relevance between returned images and user intentions (i.e., social relevance). Specifically, we propose a Markov chain based Social-Visual Ranking algorithm by taking social relevance into account. By using some extensive experiments, we demonstrated the significant and effectiveness of the proposed social-visual ranking method.

  1. Retrieving quantifiable social media data from human sensor networks for disaster modeling and crisis mapping

    Science.gov (United States)

    Aulov, Oleg

    This dissertation presents a novel approach that utilizes quantifiable social media data as a human aware, near real-time observing system, coupled with geophysical predictive models for improved response to disasters and extreme events. It shows that social media data has the potential to significantly improve disaster management beyond informing the public, and emphasizes the importance of different roles that social media can play in management, monitoring, modeling and mitigation of natural and human-caused extreme disasters. In the proposed approach Social Media users are viewed as "human sensors" that are "deployed" in the field, and their posts are considered to be "sensor observations", thus different social media outlets all together form a Human Sensor Network. We utilized the "human sensor" observations, as boundary value forcings, to show improved geophysical model forecasts of extreme disaster events when combined with other scientific data such as satellite observations and sensor measurements. Several recent extreme disasters are presented as use case scenarios. In the case of the Deepwater Horizon oil spill disaster of 2010 that devastated the Gulf of Mexico, the research demonstrates how social media data from Flickr can be used as a boundary forcing condition of GNOME oil spill plume forecast model, and results in an order of magnitude forecast improvement. In the case of Hurricane Sandy NY/NJ landfall impact of 2012, we demonstrate how the model forecasts, when combined with social media data in a single framework, can be used for near real-time forecast validation, damage assessment and disaster management. Owing to inherent uncertainties in the weather forecasts, the NOAA operational surge model only forecasts the worst-case scenario for flooding from any given hurricane. Geolocated and time-stamped Instagram photos and tweets allow near real-time assessment of the surge levels at different locations, which can validate model forecasts, give

  2. Modeling geo-homopholy in online social networks for population distribution projection

    Directory of Open Access Journals (Sweden)

    Yuanxing Zhang

    2017-09-01

    Full Text Available Purpose – Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks. Design/methodology/approach – In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions. Findings – By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time. Originality/value – This paper tries to project population distribution by modeling geo-homophily in OSNs.

  3. Social Networks and the Environment

    OpenAIRE

    Julio Videras

    2013-01-01

    This review discusses empirical research on social networks and the environment; it summarizes findings from representative studies and the conceptual frameworks social scientists use to examine the role of social networks. The article presents basic concepts in social network analysis, summarizes common challenges of empirical research on social networks, and outlines areas for future research. Finally, the article discusses the normative and positive meanings of social networks.

  4. An Introduction to Models of Online Peer-to-Peer Social Networking

    CERN Document Server

    Kesidis, George

    2010-01-01

    This book concerns peer-to-peer applications and mechanisms operating on the Internet, particularly those that are not fully automated and involve significant human interaction. So, the realm of interest is the intersection of distributed systems and online social networking. Generally, simple models are described to clarify the ideas. Beginning with short overviews of caching, graph theory and game theory, we cover the basic ideas of structured and unstructured search. We then describe a simple framework for reputations and for iterated referrals and consensus. This framework is applied to a

  5. Network-based modeling and intelligent data mining of social media for improving care.

    Science.gov (United States)

    Akay, Altug; Dragomir, Andrei; Erlandsson, Bjorn-Erik

    2015-01-01

    Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative sentiment, as well as the side effects of treatment, in users' forum posts, and identifies user communities (modules) and influential users for the purpose of ascertaining user opinion of cancer treatment. We used a self-organizing map to analyze word frequency data derived from users' forum posts. We then introduced a novel network-based approach for modeling users' forum interactions and employed a network partitioning method based on optimizing a stability quality measure. This allowed us to determine consumer opinion and identify influential users within the retrieved modules using information derived from both word-frequency data and network-based properties. Our approach can expand research into intelligently mining social media data for consumer opinion of various treatments to provide rapid, up-to-date information for the pharmaceutical industry, hospitals, and medical staff, on the effectiveness (or ineffectiveness) of future treatments.

  6. [Social networks and medicine].

    Science.gov (United States)

    Bastardot, F; Vollenweider, P; Marques-Vidal, P

    2015-11-04

    Social networks (social media or #SoMe) have entered medical practice within the last few years. These new media--like Twitter or Skype--enrich interactions among physicians (telemedicine), among physicians and patients (virtual consultations) and change the way of teaching medicine. They also entail new ethical, deontological and legal issues: the extension of the consultation area beyond the medical office and the access of information by third parties were recently debated. We develop here a review of some social networks with their characteristics, applications for medicine and limitations, and we offer some recommendations of good practice.

  7. Network Dynamics: Modeling And Generation Of Very Large Heterogeneous Social Networks

    Science.gov (United States)

    2015-11-23

    P11035 (2014). [19] P. L. Krapivsky and S. Redner, Phys. Rev. E. 71, 036118 (2005). [20] M. O. Jackson and B. W. Rogers, Amer. Econ . Rev. 97, 890...P06004 (2010). [24] M. E. J. Newman, Networks: An Introduction (Oxford Univ. Press, Oxford, 2010). [25] P. J. Flory, Principles of Polymer Chemistry

  8. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  9. Modeling the effects of social impact on epidemic spreading in complex networks

    Science.gov (United States)

    Ni, Shunjiang; Weng, Wenguo; Zhang, Hui

    2011-11-01

    We investigate by mean-field analysis and extensive simulations the effects of social impact on epidemic spreading in various typical networks with two types of nodes: active nodes and passive nodes, of which the behavior patterns are modeled according to the social impact theory. In this study, nodes are not only the media to spread the virus, but also disseminate their opinions on the virus-whether there is a need for certain self-protection measures to be taken to reduce the risk of being infected. Our results indicate that the interaction between epidemic spreading and opinion dynamics can have significant influences on the spreading of infectious diseases and related applications, such as the implementation of prevention and control measures against the infectious diseases.

  10. Multi-level policies and adaptive social networks – a conceptual modeling study for maintaining a polycentric governance system

    Directory of Open Access Journals (Sweden)

    Jean-Denis Mathias

    2017-03-01

    Full Text Available Information and collaboration patterns embedded in social networks play key roles in multilevel and polycentric modes of governance. However, modeling the dynamics of such social networks in multilevel settings has been seldom addressed in the literature. Here we use an adaptive social network model to elaborate the interplay between a central and a local government in order to maintain a polycentric governance. More specifically, our analysis explores in what ways specific policy choices made by a central agent affect the features of an emerging social network composed of local organizations and local users. Using two types of stylized policies, adaptive co-management and adaptive one-level management, we focus on the benefits of multi-level adaptive cooperation for network management. Our analysis uses viability theory to explore and to quantify the ability of these policies to achieve specific network properties. Viability theory gives the family of policies that enables maintaining the polycentric governance unlike optimal control that gives a unique blueprint. We found that the viability of the policies can change dramatically depending on the goals and features of the social network. For some social networks, we also found a very large difference between the viability of the adaptive one-level management and adaptive co-management policies. However, results also show that adaptive co-management doesn’t always provide benefits. Hence, we argue that applying viability theory to governance networks can help policy design by analyzing the trade-off between the costs of adaptive co-management and the benefits associated with its ability to maintain desirable social network properties in a polycentric governance framework.

  11. Social exchange: Relations and networks

    OpenAIRE

    Dijkstra, Jacob

    2015-01-01

    In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network research. The paper provides an accessible entry into the literature on social exchange.

  12. Privacy in social networking sites

    OpenAIRE

    Λεονάρδος, Γεώργιος; Leonardos, Giorgos

    2016-01-01

    The purpose of this study is to explore the aspects of privacy over the use of social networks web sites. More specific, we will show the types of social networks, their privacy mechanisms that are different in each social network site, their privacy options that are offered to users. We will report some serious privacy violations incidents of the most popular social networks sites such as Facebook, Twitter, LinkedIn. Also, we will report some important surveys about social networks and pr...

  13. The SIS Model of Epidemic Spreading in a Hierarchical Social Network

    International Nuclear Information System (INIS)

    Grabowski, A.; Kosinski, R.A.

    2005-01-01

    The phenomenon of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The SIS model with temporal immunity to a disease and a time of incubation is used. In our model spatial localization of individuals belonging to different social groups, effectiveness of different interpersonal interactions and the mobility of a contemporary community are taken into account. The structure of interpersonal connections is based on a scale-free network. The influence of the structure of the social network on typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, is discussed. The probability that endemic state occurs is also calculated. Surprisingly it occurs, that less contagious diseases has greater chance to survive. The influence of preventive vaccinations on the spreading process is investigated and critical range of vaccinations that is sufficient for the suppression of an epidemic is calculated. Our results of numerical calculations are compared with the solutions of the master equation for the spreading process, and good agreement is found. (author)

  14. Online Advertising in Social Networks

    Science.gov (United States)

    Bagherjeiran, Abraham; Bhatt, Rushi P.; Parekh, Rajesh; Chaoji, Vineet

    Online social networks offer opportunities to analyze user behavior and social connectivity and leverage resulting insights for effective online advertising. This chapter focuses on the role of social network information in online display advertising.

  15. Philosophy of social networking

    Directory of Open Access Journals (Sweden)

    Markova T. V.

    2018-04-01

    Full Text Available the article is devoted to the study of social networks impact on an individual, which are an important part of a modern society. Through reflections the reasons of the popularity of the phenomenon of virtual communication in the 21st century are determined: what drives a person when he / she registers on the sites for communication, premises for his / her actions and consequences. The latter is viewed from both a social and a personal point of view. After analyzing the charts of social networks popularity, the authors come to the conclusion that there is an increase in the population of the virtual communication supporters. It allows to assert that the problem of the termination of live communication is relevant to this day. Dualism of social networks influence on the consciousness of an individual is stated: together with negative consequences positive aspects are considered. By analyzing social media researches, as well as by the means of a survey, the dominant reason for the world wide web entering is identified. After that, it is clearly shown what a typical site for communication is; as a result, the pros and cons of such time spending are specified. The conclusion states the predominance of the Internet dependence over the other types of dependencies, also forecasts are made for the future of both social networks and the people caught in their web.

  16. A Cloud Theory-Based Trust Computing Model in Social Networks

    Directory of Open Access Journals (Sweden)

    Fengming Liu

    2016-12-01

    Full Text Available How to develop a trust management model and then to efficiently control and manage nodes is an important issue in the scope of social network security. In this paper, a trust management model based on a cloud model is proposed. The cloud model uses a specific computation operator to achieve the transformation from qualitative concepts to quantitative computation. Additionally, this can also be used to effectively express the fuzziness, randomness and the relationship between them of the subjective trust. The node trust is divided into reputation trust and transaction trust. In addition, evaluation methods are designed, respectively. Firstly, the two-dimension trust cloud evaluation model is designed based on node’s comprehensive and trading experience to determine the reputation trust. The expected value reflects the average trust status of nodes. Then, entropy and hyper-entropy are used to describe the uncertainty of trust. Secondly, the calculation methods of the proposed direct transaction trust and the recommendation transaction trust involve comprehensively computation of the transaction trust of each node. Then, the choosing strategies were designed for node to trade based on trust cloud. Finally, the results of a simulation experiment in P2P network file sharing on an experimental platform directly reflect the objectivity, accuracy and robustness of the proposed model, and could also effectively identify the malicious or unreliable service nodes in the system. In addition, this can be used to promote the service reliability of the nodes with high credibility, by which the stability of the whole network is improved.

  17. Adolescents' Social Network Site Use, Peer Appearance-Related Feedback, and Body Dissatisfaction: Testing a Mediation Model.

    Science.gov (United States)

    de Vries, Dian A; Peter, Jochen; de Graaf, Hanneke; Nikken, Peter

    2016-01-01

    Previous correlational research indicates that adolescent girls who use social network sites more frequently are more dissatisfied with their bodies. However, we know little about the causal direction of this relationship, the mechanisms underlying this relationship, and whether this relationship also occurs among boys to the same extent. The present two-wave panel study (18 month time lag) among 604 Dutch adolescents (aged 11-18; 50.7% female; 97.7% native Dutch) aimed to fill these gaps in knowledge. Structural equation modeling showed that social network site use predicted increased body dissatisfaction and increased peer influence on body image in the form of receiving peer appearance-related feedback. Peer appearance-related feedback did not predict body dissatisfaction and thus did not mediate the effect of social network site use on body dissatisfaction. Gender did not moderate the findings. Hence, social network sites can play an adverse role in the body image of both adolescent boys and girls.

  18. A Web Service-based framework model for people-centric sensing applications applied to social networking.

    Science.gov (United States)

    Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

    2012-01-01

    As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype.

  19. The Social Network Classroom

    Science.gov (United States)

    Bunus, Peter

    Online social networking is an important part in the everyday life of college students. Despite the increasing popularity of online social networking among students and faculty members, its educational benefits are largely untested. This paper presents our experience in using social networking applications and video content distribution websites as a complement of traditional classroom education. In particular, the solution has been based on effective adaptation, extension and integration of Facebook, Twitter, Blogger YouTube and iTunes services for delivering educational material to students on mobile platforms like iPods and 3 rd generation mobile phones. The goals of the proposed educational platform, described in this paper, are to make the learning experience more engaging, to encourage collaborative work and knowledge sharing among students, and to provide an interactive platform for the educators to reach students and deliver lecture material in a totally new way.

  20. A social network model for the development of a 'Theory of Mind'

    Science.gov (United States)

    Harré, Michael S.

    2013-02-01

    A "Theory of Mind" is one of the most important skills we as humans have developed; It enables us to infer the mental states and intentions of others, build stable networks of relationships and it plays a central role in our psychological make-up and development. Findings published earlier this year have also shown that we as a species as well as each of us individually benefit from the enlargement of the underlying neuro-anatomical regions that support our social networks, mediated by our Theory of Mind that stabilises these networks. On the basis of such progress and that of earlier work, this paper draws together several different strands from psychology, behavioural economics and network theory in order to generate a novel theoretical representation of the development of our social-cognition and how subsequent larger social networks enables much of our cultural development but at the increased risk of mental disorders.

  1. Spreading gossip in social networks

    Science.gov (United States)

    Lind, Pedro G.; da Silva, Luciano R.; Andrade, José S., Jr.; Herrmann, Hans J.

    2007-09-01

    We study a simple model of information propagation in social networks, where two quantities are introduced: the spread factor, which measures the average maximal reachability of the neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such a fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.

  2. Spreading gossip in social networks.

    Science.gov (United States)

    Lind, Pedro G; da Silva, Luciano R; Andrade, José S; Herrmann, Hans J

    2007-09-01

    We study a simple model of information propagation in social networks, where two quantities are introduced: the spread factor, which measures the average maximal reachability of the neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such a fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.

  3. Psychosocial characteristics and social networks of suicidal prisoners: towards a model of suicidal behaviour in detention.

    Directory of Open Access Journals (Sweden)

    Adrienne Rivlin

    Full Text Available Prisoners are at increased risk of suicide. Investigation of both individual and environmental risk factors may assist in developing suicide prevention policies for prisoners and other high-risk populations. We conducted a matched case-control interview study with 60 male prisoners who had made near-lethal suicide attempts in prison (cases and 60 male prisoners who had not (controls. We compared levels of depression, hopelessness, self-esteem, impulsivity, aggression, hostility, childhood abuse, life events (including events occurring in prison, social support, and social networks in univariate and multivariate models. A range of psychosocial factors was associated with near-lethal self-harm in prisoners. Compared with controls, cases reported higher levels of depression, hopelessness, impulsivity, and aggression, and lower levels of self-esteem and social support (all p values <0.001. Adverse life events and criminal history factors were also associated with near-lethal self-harm, especially having a prior prison spell and having been bullied in prison, both of which remained significant in multivariate analyses. The findings support a model of suicidal behaviour in prisoners that incorporates imported vulnerability factors, clinical factors, and prison experiences, and underscores their interaction. Strategies to reduce self-harm and suicide in prisoners should include attention to such factors.

  4. A simplistic model for identifying prominent web users in directed multiplex social networks: a case study using Twitter networks

    Science.gov (United States)

    Loucif, Hemza; Boubetra, Abdelhak; Akrouf, Samir

    2016-10-01

    This paper aims to describe a new simplistic model dedicated to gauge the online influence of Twitter users based on a mixture of structural and interactional features. The model is an additive mathematical formulation which involves two main parts. The first part serves to measure the influence of the Twitter user on just his neighbourhood covering his followers. However, the second part evaluates the potential influence of the Twitter user beyond the circle of his followers. Particularly, it measures the likelihood that the tweets of the Twitter user will spread further within the social graph through the retweeting process. The model is tested on a data set involving four kinds of real-world egocentric networks. The empirical results reveal that an active ordinary user is more prominent than a non-active celebrity one. A simple comparison is conducted between the proposed model and two existing simplistic approaches. The results show that our model generates the most realistic influence scores due to its dealing with both explicit (structural and interactional) and implicit features.

  5. Peer-Learning Networks in Social Work Doctoral Education: An Interdisciplinary Model

    Science.gov (United States)

    Miller, J. Jay; Duron, Jacquelynn F.; Bosk, Emily Adlin; Finno-Velasquez, Megan; Abner, Kristin S.

    2016-01-01

    Peer-learning networks (PLN) can be valuable tools for doctoral students. Participation in these networks can aid in the completion of the dissertation, lead to increased scholarship productivity, and assist in student retention. Yet, despite the promise of PLNs, few studies have documented their effect on social work doctoral education. This…

  6. Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

    Science.gov (United States)

    Firdausiah Mansur, Andi Besse; Yusof, Norazah

    2013-01-01

    Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

  7. A Social Network Analysis of Occupational Segregation

    DEFF Research Database (Denmark)

    Buhai, Ioan Sebastian; van der Leij, Marco

    We develop a social network model of occupational segregation between different social groups, generated by the existence of positive inbreeding bias among individuals from the same group. If network referrals are important for job search, then expected homophily in the contact network structure...

  8. Influence maximization in social networks under an independent cascade-based model

    Science.gov (United States)

    Wang, Qiyao; Jin, Yuehui; Lin, Zhen; Cheng, Shiduan; Yang, Tan

    2016-02-01

    The rapid growth of online social networks is important for viral marketing. Influence maximization refers to the process of finding influential users who make the most of information or product adoption. An independent cascade-based model for influence maximization, called IMIC-OC, was proposed to calculate positive influence. We assumed that influential users spread positive opinions. At the beginning, users held positive or negative opinions as their initial opinions. When more users became involved in the discussions, users balanced their own opinions and those of their neighbors. The number of users who did not change positive opinions was used to determine positive influence. Corresponding influential users who had maximum positive influence were then obtained. Experiments were conducted on three real networks, namely, Facebook, HEP-PH and Epinions, to calculate maximum positive influence based on the IMIC-OC model and two other baseline methods. The proposed model resulted in larger positive influence, thus indicating better performance compared with the baseline methods.

  9. Social exchange : Relations and networks

    NARCIS (Netherlands)

    Dijkstra, Jacob

    2015-01-01

    In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network

  10. Communication in Animal Social Networks

    NARCIS (Netherlands)

    Snijders, Lysanne; Naguib, Marc

    2017-01-01

    Animal social networks and animal communication networks are key disciplines for understanding animal social behavior, yet these disciplines remain poorly integrated. In this review, we show how communication and social networks are inherently linked, with social signals reflecting and affecting

  11. Analytical Solutions for Rumor Spreading Dynamical Model in a Social Network

    Science.gov (United States)

    Fallahpour, R.; Chakouvari, S.; Askari, H.

    2015-03-01

    In this paper, Laplace Adomian decomposition method is utilized for evaluating of spreading model of rumor. Firstly, a succinct review is constructed on the subject of using analytical methods such as Adomian decomposion method, Variational iteration method and Homotopy Analysis method for epidemic models and biomathematics. In continue a spreading model of rumor with consideration of forgetting mechanism is assumed and subsequently LADM is exerted for solving of it. By means of the aforementioned method, a general solution is achieved for this problem which can be readily employed for assessing of rumor model without exerting any computer program. In addition, obtained consequences for this problem are discussed for different cases and parameters. Furthermore, it is shown the method is so straightforward and fruitful for analyzing equations which have complicated terms same as rumor model. By employing numerical methods, it is revealed LADM is so powerful and accurate for eliciting solutions of this model. Eventually, it is concluded that this method is so appropriate for this problem and it can provide researchers a very powerful vehicle for scrutinizing rumor models in diverse kinds of social networks such as Facebook, YouTube, Flickr, LinkedIn and Tuitor.

  12. Social network and addiction.

    Science.gov (United States)

    La Barbera, Daniele; La Paglia, Filippo; Valsavoia, Rosaria

    2009-01-01

    In recent decades, the rapid development of innovative Internet-based communication technologies created a new field of academic study among scholars. Particularly, the attention of researchers is focusing on new ways to form relationship-thought social web. Social Network sites constitute a new form of web communities, where people meet and share interests and activities. Due to exponential growth of these sites, an increasing number of scholars are beginning to study the emergent phenomena in order to identify any psychopathological risk related to use of social web, such as addiction. This article examines the recent literature about this issue.

  13. PSN: Portfolio Social Network

    DEFF Research Database (Denmark)

    Cortes, Jordi Magrina; Nizamani, Sarwat; Memon, Nasrullah

    2014-01-01

    In this paper we present a web-based information system which is a portfolio social network (PSN) that provides solutions to the recruiters and job seekers. The proposed system enables users to create portfolio so that he/she can add his specializations with piece of code if any specifically...

  14. Foraging Online Social Networks

    NARCIS (Netherlands)

    Koot, G.; Huis in ’t Veld, M.A.A.; Hendricksen, J.; Vries, A. de; Broek, E.L. van den

    2014-01-01

    A concise and practical introduction is given on Online Social Networks (OSN) and their application in law enforcement, including a brief survey of related work. Subsequently, a tool is introduced that can be used to search OSN in order to generate user profiles. Both its architecture and processing

  15. Change Detection in Social Networks

    National Research Council Canada - National Science Library

    McCulloh, Ian; Webb, Matthew; Graham, John; Carley, Kathleen; Horn, Daniel B

    2008-01-01

    .... This project proposes a new method for detecting change in social networks over time, by applying a cumulative sum statistical process control statistic to normally distributed network measures...

  16. Psychosocial Characteristics and Social Networks of Suicidal Prisoners: Towards a Model of Suicidal Behaviour in Detention

    Science.gov (United States)

    Rivlin, Adrienne; Hawton, Keith; Marzano, Lisa; Fazel, Seena

    2013-01-01

    Prisoners are at increased risk of suicide. Investigation of both individual and environmental risk factors may assist in developing suicide prevention policies for prisoners and other high-risk populations. We conducted a matched case-control interview study with 60 male prisoners who had made near-lethal suicide attempts in prison (cases) and 60 male prisoners who had not (controls). We compared levels of depression, hopelessness, self-esteem, impulsivity, aggression, hostility, childhood abuse, life events (including events occurring in prison), social support, and social networks in univariate and multivariate models. A range of psychosocial factors was associated with near-lethal self-harm in prisoners. Compared with controls, cases reported higher levels of depression, hopelessness, impulsivity, and aggression, and lower levels of self-esteem and social support (all p values suicidal behaviour in prisoners that incorporates imported vulnerability factors, clinical factors, and prison experiences, and underscores their interaction. Strategies to reduce self-harm and suicide in prisoners should include attention to such factors. PMID:23922671

  17. Online Social Network Interactions:

    Directory of Open Access Journals (Sweden)

    Hui-Jung Chang

    2018-01-01

    Full Text Available A cross-cultural comparison of social networking structure on McDonald’s Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald’s Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald’s Facebook fan network has more fans, while Taiwan’s McDonald’s Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

  18. Global maize trade and food security: implications from a social network model.

    Science.gov (United States)

    Wu, Felicia; Guclu, Hasan

    2013-12-01

    In this study, we developed a social network model of the global trade of maize: one of the most important food, feed, and industrial crops worldwide, and critical to food security. We used this model to analyze patterns of maize trade among nations, and to determine where vulnerabilities in food security might arise if maize availability was decreased due to factors such as diversion to nonfood uses, climatic factors, or plant diseases. Using data on imports and exports from the U.N. Commodity Trade Statistics Database for each year from 2000 to 2009 inclusive, we summarized statistics on volumes of maize trade between pairs of nations for 217 nations. There is evidence of market segregation among clusters of nations; with three prominent clusters representing Europe, Brazil and Argentina, and the United States. The United States is by far the largest exporter of maize worldwide, whereas Japan and the Republic of Korea are the largest maize importers. In particular, the star-shaped cluster of the network that represents U.S. maize trade to other nations indicates the potential for food security risks because of the lack of trade these other nations conduct with other maize exporters. If a scenario arose in which U.S. maize could not be exported in as large quantities, maize supplies in many nations could be jeopardized. We discuss this in the context of recent maize ethanol production and its attendant impacts on food prices elsewhere worldwide. © 2013 Society for Risk Analysis.

  19. Latent Space Approaches to Social Network Analysis

    National Research Council Canada - National Science Library

    Hoff, Peter D; Raftery, Adrian E; Handcock, Mark S

    2001-01-01

    .... In studies of social networks, recent emphasis has been placed on random graph models where the nodes usually represent individual social actors and the edges represent the presence of a specified...

  20. Defining social inclusion of people with intellectual and developmental disabilities: an ecological model of social networks and community participation.

    Science.gov (United States)

    Simplican, Stacy Clifford; Leader, Geraldine; Kosciulek, John; Leahy, Michael

    2015-03-01

    Social inclusion is an important goal for people with intellectual and developmental disabilities, families, service providers, and policymakers; however, the concept of social inclusion remains unclear, largely due to multiple and conflicting definitions in research and policy. We define social inclusion as the interaction between two major life domains: interpersonal relationships and community participation. We then propose an ecological model of social inclusion that includes individual, interpersonal, organizational, community, and socio-political factors. We identify four areas of research that our ecological model of social inclusion can move forward: (1) organizational implementation of social inclusion; (2) social inclusion of people with intellectual and developmental disabilities living with their families, (3) social inclusion of people along a broader spectrum of disability, and (4) the potential role of self-advocacy organizations in promoting social inclusion. Copyright © 2014. Published by Elsevier Ltd.

  1. Promoting Social Network Awareness: A Social Network Monitoring System

    Science.gov (United States)

    Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

    2010-01-01

    To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

  2. Social network analysis via multi-state reliability and conditional influence models

    International Nuclear Information System (INIS)

    Schneider, Kellie; Rainwater, Chase; Pohl, Ed; Hernandez, Ivan; Ramirez-Marquez, Jose Emmanuel

    2013-01-01

    This paper incorporates multi-state reliability measures into the assessment of a social network in which influence is treated as a multi-state commodity that flows through the network. The reliability of the network is defined as the probability that at least a certain level of influence reaches an intended target. We consider an individual's influence level as a function of the influence levels received from preceding actors in the network. We define several communication functions which describe the level of influence a particular actor will pass along to other actors within the network. Illustrative examples are presented, and the network reliability under the various communication influence levels is computed using exhaustive enumeration for a small example and Monte Carlo simulation for larger, more realistic sized examples.

  3. Information and influence propagation in social networks

    CERN Document Server

    Chen, Wei; Lakshmanan, Laks V S

    2013-01-01

    Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models

  4. Individual Search and Social Networks

    OpenAIRE

    Sanjeev Goyal; Stephanie Rosenkranz; Utz Weitzel; Vincent Buskens

    2014-01-01

    The explosion in online social networks motivates an enquiry into their structure and their welfare effects. A central feature of these networks is information sharing: online social networks lower the cost of getting information from others. These lower costs affect the attractiveness of individual search vis-a-vis a reliance on social networks. The paper reports the findings of an experiment on these effects. Our experiment shows that online networks can have large effects. Information acqu...

  5. Fitting Social Network Models Using Varying Truncation Stochastic Approximation MCMC Algorithm

    KAUST Repository

    Jin, Ick Hoon

    2013-10-01

    The exponential random graph model (ERGM) plays a major role in social network analysis. However, parameter estimation for the ERGM is a hard problem due to the intractability of its normalizing constant and the model degeneracy. The existing algorithms, such as Monte Carlo maximum likelihood estimation (MCMLE) and stochastic approximation, often fail for this problem in the presence of model degeneracy. In this article, we introduce the varying truncation stochastic approximation Markov chain Monte Carlo (SAMCMC) algorithm to tackle this problem. The varying truncation mechanism enables the algorithm to choose an appropriate starting point and an appropriate gain factor sequence, and thus to produce a reasonable parameter estimate for the ERGM even in the presence of model degeneracy. The numerical results indicate that the varying truncation SAMCMC algorithm can significantly outperform the MCMLE and stochastic approximation algorithms: for degenerate ERGMs, MCMLE and stochastic approximation often fail to produce any reasonable parameter estimates, while SAMCMC can do; for nondegenerate ERGMs, SAMCMC can work as well as or better than MCMLE and stochastic approximation. The data and source codes used for this article are available online as supplementary materials. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  6. The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

    OpenAIRE

    Blower, Sally; Go, Myong-Hyun

    2011-01-01

    Abstract Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagu...

  7. Stable configurations in social networks

    Science.gov (United States)

    Bronski, Jared C.; DeVille, Lee; Ferguson, Timothy; Livesay, Michael

    2018-06-01

    We present and analyze a model of opinion formation on an arbitrary network whose dynamics comes from a global energy function. We study the global and local minimizers of this energy, which we call stable opinion configurations, and describe the global minimizers under certain assumptions on the friendship graph. We show a surprising result that the number of stable configurations is not necessarily monotone in the strength of connection in the social network, i.e. the model sometimes supports more stable configurations when the interpersonal connections are made stronger.

  8. Social Networks and Political Parties in Chile

    OpenAIRE

    Adler Lomnitz, Larissa

    2002-01-01

    This paper describes the origin and evolution of two Chilean political parties (the Radical Party and the Christian Democrat Party) through the analysis of the social networks that originated and composed them. The aim of this study is to propose a model of national political cultures on the basis of the structure of social networks related to power and of the symbol system, which legitimizes it. The structure of social networks, horizontal and vertical, are based on reciprocal or redistribut...

  9. An Automatic User Grouping Model for a Group Recommender System in Location-Based Social Networks

    Directory of Open Access Journals (Sweden)

    Elahe Khazaei

    2018-02-01

    Full Text Available Spatial group recommendation refers to suggesting places to a given set of users. In a group recommender system, members of a group should have similar preferences in order to increase the level of satisfaction. Location-based social networks (LBSNs provide rich content, such as user interactions and location/event descriptions, which can be leveraged for group recommendations. In this paper, an automatic user grouping model is introduced that obtains information about users and their preferences through an LBSN. The preferences of the users, proximity of the places the users have visited in terms of spatial range, users’ free days, and the social relationships among users are extracted automatically from location histories and users’ profiles in the LBSN. These factors are combined to determine the similarities among users. The users are partitioned into groups based on these similarities. Group size is the key to coordinating group members and enhancing their satisfaction. Therefore, a modified k-medoids method is developed to cluster users into groups with specific sizes. To evaluate the efficiency of the proposed method, its mean intra-cluster distance and its distribution of cluster sizes are compared to those of general clustering algorithms. The results reveal that the proposed method compares favourably with general clustering approaches, such as k-medoids and spectral clustering, in separating users into groups of a specific size with a lower mean intra-cluster distance.

  10. Coupling ecological and social network models to assess “transmission” and “contagion” of an aquatic invasive species

    Science.gov (United States)

    Haak, Danielle M.; Fath, Brian D.; Forbes, Valery E.; Martin, Dustin R.; Pope, Kevin L.

    2017-01-01

    Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensisalters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

  11. Transition and Social networks

    OpenAIRE

    Raghavan, Raghu; Pawson, N.

    2011-01-01

    School leavers with learning disabilities often face difficulties in making a smooth transition from school to college, employment or more broadly, to adult life. The transition phase is traumatic for the young person with learning disabilities and their families as it often results in the loss of friendships, relationships and social networks. The aim of this chapter is to explore the issues of transition from adolescence to adulthood for young people with learning disabilities and its effe...

  12. Social networks: communication and change

    Directory of Open Access Journals (Sweden)

    Gustavo Cardoso

    2011-01-01

    Full Text Available Virtual social networks have brought about the possibility for open and plural debate, where all those with the necessary literacy skills and means are able to participate in the creation and dissemination of information. By pressing political agents and determining the “agenda” of a lot of the media, users demonstrate that we stand at an ideal platform for creating both real social movements and more or less fleeting events, as manifestos or virtual campaigns. Nonetheless, in order to understand the role of virtual social networks in today’s world, we need to answer some prior questions. Are we facing a new communication model, whereby the product of “disinterested” interactivity creates an aura of confidence in disseminated information, often quite higher that that seen in the “old media”? Will that interactivity be a chance to fight-off citizens’ growing detachment with regard to the “res publica”? Will we find in citizen-made journalism, transmitted through virtual social networks, the consecration of a true fourth power? On the other hand, can we call the distinct collective movements we have seen emerging true “social movements”?The present article aims to examine this and other issues that come to the fore in the intricate social world of cyberspace.

  13. Sustainability and collapse in a coevolutionary model of local resource stocks and behavioral patterns on a social network

    Science.gov (United States)

    Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Kurths, Jürgen

    2014-05-01

    When investigating the causes and consequences of global change, the collective behavior of human beings is considered as having a considerable impact on natural systems. In our work, we propose a conceptual coevolutionary model simulating the dynamics of local renewable resources in interaction with simplistic societal agents exploiting those resources. The society is represented by a social network on which social traits may be transmitted between agents. These traits themselves induce a certain rate of exploitation of the resource, leading either to its depletion or sustainable existence. Traits are exchanged probabilistically according to their instantaneous individual payoff, and hence this process depends on the status of the natural resource. At the same time agents may adaptively restructure their set of acquaintances. Connections with agents having a different trait may be broken while new connections with agents of the same trait are established. We investigate which choices of social parameters, like the frequency of social interaction, rationality and rate of social network adaptation, cause the system to end in a sustainable state and, hence, what can be done to avoid a collapse of the entire system. The importance and influence of the social network structure is analyzed by the variation of link-densities in the underlying network topology and shows significant influence on the expected outcome of the model. For a static network with no adaptation we find a robust phase transition between the two different regimes, sustainable and non-sustainable, which co-exist in parameter space. High connectivity within the social network, e.g., high link-densities, in combination with a fast rate of social learning lead to a likely collapse of the entire co-evolutionary system, whereas slow learning and small network connectivity very likely result in the sustainable existence of the natural resources. Collapse may be avoided by an intelligent rewiring, e

  14. Collectivism culture, HIV stigma and social network support in Anhui, China: a path analytic model.

    Science.gov (United States)

    Zang, Chunpeng; Guida, Jennifer; Sun, Yehuan; Liu, Hongjie

    2014-08-01

    HIV stigma is rooted in culture and, therefore, it is essential to investigate it within the context of culture. The objective of this study was to examine the interrelationships among individualism-collectivism, HIV stigma, and social network support. A social network study was conducted among 118 people living with HIVAIDS in China, who were infected by commercial plasma donation, a nonstigmatized behavior. The Individualism-Collectivism Interpersonal Assessment Inventory (ICIAI) was used to measure cultural norms and values in the context of three social groups, family members, friends, and neighbors. Path analyses revealed (1) a higher level of family ICIAI was significantly associated with a higher level of HIV self-stigma (β=0.32); (2) a higher level of friend ICIAI was associated with a lower level of self-stigma (β=-035); (3) neighbor ICIAI was associated with public stigma (β=-0.61); (4) self-stigman was associated with social support from neighbors (β=-0.27); and (5) public stigma was associated with social support from neighbors (β=-0.24). This study documents that HIV stigma may mediate the relationship between collectivist culture and social network support, providing an empirical basis for interventions to include aspects of culture into HIV intervention strategies.

  15. New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

    Science.gov (United States)

    Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

    2012-01-21

    Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction

  16. Modeling individual and collective opinion in online social networks: drivers of choice behavior and effects of marketing interventions

    NARCIS (Netherlands)

    Koster, S.E.; Langley, D.J.

    2013-01-01

    We investigate factors influencing choice behavior in online social networks. We use twitter data from a Dutch television talent show. In study one, we implement a nested conditional logit model with latent classes. We find heterogeneous effects. For two latent classes, cognitive factors most

  17. Social structure of Facebook networks

    Science.gov (United States)

    Traud, Amanda L.; Mucha, Peter J.; Porter, Mason A.

    2012-08-01

    We study the social structure of Facebook “friendship” networks at one hundred American colleges and universities at a single point in time, and we examine the roles of user attributes-gender, class year, major, high school, and residence-at these institutions. We investigate the influence of common attributes at the dyad level in terms of assortativity coefficients and regression models. We then examine larger-scale groupings by detecting communities algorithmically and comparing them to network partitions based on user characteristics. We thereby examine the relative importance of different characteristics at different institutions, finding for example that common high school is more important to the social organization of large institutions and that the importance of common major varies significantly between institutions. Our calculations illustrate how microscopic and macroscopic perspectives give complementary insights on the social organization at universities and suggest future studies to investigate such phenomena further.

  18. Networking for philanthropy: increasing volunteer behavior via social networking sites.

    Science.gov (United States)

    Kim, Yoojung; Lee, Wei-Na

    2014-03-01

    Social networking sites (SNSs) provide a unique social venue to engage the young generation in philanthropy through their networking capabilities. An integrated model that incorporates social capital into the Theory of Reasoned Action is developed to explain volunteer behavior through social networks. As expected, volunteer behavior was predicted by volunteer intention, which was influenced by attitudes and subjective norms. In addition, social capital, an outcome of the extensive use of SNSs, was as an important driver of users' attitude and subjective norms toward volunteering via SNSs.

  19. Social network analysis community detection and evolution

    CERN Document Server

    Missaoui, Rokia

    2015-01-01

    This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edit

  20. Data mining for social network data

    CERN Document Server

    Memon, Nasrullah; Hicks, David L; Chen, Hsinchun

    2010-01-01

    Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on ""Data Mining for Social Network Data"" will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, and activities in open fora, and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution

  1. Interests diffusion in social networks

    Science.gov (United States)

    D'Agostino, Gregorio; D'Antonio, Fulvio; De Nicola, Antonio; Tucci, Salvatore

    2015-10-01

    We provide a model for diffusion of interests in Social Networks (SNs). We demonstrate that the topology of the SN plays a crucial role in the dynamics of the individual interests. Understanding cultural phenomena on SNs and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a procedure to infer members' interests; and an interests evolution theory to predict how the interests propagate in the network. As a result, one achieves an analytic tool to measure individual features, such as members' susceptibilities and authorities. Although the approach applies to any type of social network, here it is has been tested against the computer science research community. The DBLP (Digital Bibliography and Library Project) database has been elected as test-case since it provides the most comprehensive list of scientific production in this field.

  2. Testing knowledge sharing effectiveness: trust, motivation, leadership style, workplace spirituality and social network embedded model

    Directory of Open Access Journals (Sweden)

    Rahman Muhammad Sabbir

    2015-12-01

    Full Text Available The aim of this inquiry is to investigate the relationships among the antecedents of knowledge sharing effectiveness under the position of non-academic staff of higher learning institutions through an empirical test of a conceptual model consisting of trust, extrinsic and intrinsic motivation, leadership style, workplace spirituality and online social network. This study used the respondents from the non-academic staff of higher learning institutions in Malaysia (n = 200, utilizing a self-administered survey questionnaire. The structural equation modeling approach was used to test the proposed hypotheses. The outcomes indicate that all the antecedents play a substantial function in knowledge sharing effectiveness. In addition, perceived risk plays a mediating role between trust and knowledge sharing effectiveness. On the other hand, this research also proved the communication skill also plays a mediating role between leadership style and knowledge sharing effectiveness. This study contributes to pioneering empirical findings on knowledge sharing literature under the scope of the non-academic staff perspective.

  3. Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

    Science.gov (United States)

    Kim, Seungjoo

    2014-01-01

    There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information. PMID:25374943

  4. Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

    Directory of Open Access Journals (Sweden)

    Seungsoo Baek

    2014-01-01

    Full Text Available There has been an explosive increase in the population of the OSN (online social network in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information.

  5. Social Networking Sites in Education

    OpenAIRE

    Suková, Lenka

    2010-01-01

    Diploma thesis deals with social networking sites and their use in education. Thesis is divided into two general parts. The first part deals with theory of learning; Bloom's taxonomy of educational objectives and new educational theory based on learning in networks -- Connectivism. After that thesis focuses on the definition of social networking sites, introduction of some of the best known social networking sites and examples of their use in foreign and domestic educational practice. The sec...

  6. Conceptualizing of Social Networking Sites

    OpenAIRE

    J. S. Sodhi; Shilpi Sharma

    2012-01-01

    People often move to their friends, families and colleagues when they feel urge and having doubts or queries to solve. Participation in social networking site has dramatically increased in recent years. Many social networking sites boost with million of members using their network on regular basis to communicate, share , create and collaborate with others. In this paper we explore the phenomenon of using social networking site to trace a link of the search from the community of users for bett...

  7. The Semantic Network Model of Creativity: Analysis of Online Social Media Data

    Science.gov (United States)

    Yu, Feng; Peng, Theodore; Peng, Kaiping; Zheng, Sam Xianjun; Liu, Zhiyuan

    2016-01-01

    The central hypothesis of Semantic Network Model of Creativity is that creative people, who are exposed to more information that are both novel and useful, will have more interconnections between event schemas in their associations. The networks of event schemas in creative people's minds were expected to be wider and denser than those in less…

  8. Leveraging social networks for toxicovigilance.

    Science.gov (United States)

    Chary, Michael; Genes, Nicholas; McKenzie, Andrew; Manini, Alex F

    2013-06-01

    The landscape of drug abuse is shifting. Traditional means of characterizing these changes, such as national surveys or voluntary reporting by frontline clinicians, can miss changes in usage the emergence of novel drugs. Delays in detecting novel drug usage patterns make it difficult to evaluate public policy aimed at altering drug abuse. Increasingly, newer methods to inform frontline providers to recognize symptoms associated with novel drugs or methods of administration are needed. The growth of social networks may address this need. The objective of this manuscript is to introduce tools for using data from social networks to characterize drug abuse. We outline a structured approach to analyze social media in order to capture emerging trends in drug abuse by applying powerful methods from artificial intelligence, computational linguistics, graph theory, and agent-based modeling. First, we describe how to obtain data from social networks such as Twitter using publicly available automated programmatic interfaces. Then, we discuss how to use artificial intelligence techniques to extract content useful for purposes of toxicovigilance. This filtered content can be employed to generate real-time maps of drug usage across geographical regions. Beyond describing the real-time epidemiology of drug abuse, techniques from computational linguistics can uncover ways that drug discussions differ from other online conversations. Next, graph theory can elucidate the structure of networks discussing drug abuse, helping us learn what online interactions promote drug abuse and whether these interactions differ among drugs. Finally, agent-based modeling relates online interactions to psychological archetypes, providing a link between epidemiology and behavior. An analysis of social media discussions about drug abuse patterns with computational linguistics, graph theory, and agent-based modeling permits the real-time monitoring and characterization of trends of drugs of abuse. These

  9. Signed Networks in Social Media

    OpenAIRE

    Leskovec, Jure; Huttenlocher, Daniel; Kleinberg, Jon

    2010-01-01

    Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the interplay between positive and negative relationships affects the structure of on-line social networks. We connect our analyses to theories of signed networks from social psychology. We find that the c...

  10. Collective Learning in Games through Social Networks

    NARCIS (Netherlands)

    Kosterman, S.; Gierasimczuk, N.; Armentano, M.G.; Monteserin, A.; Tang, J.; Yannibelli, V.

    2015-01-01

    This paper argues that combining social networks communication and games can positively influence the learning behavior of players. We propose a computational model that combines features of social network learning (communication) and game-based learning (strategy reinforcement). The focus is on

  11. Spreading in online social networks: the role of social reinforcement.

    Science.gov (United States)

    Zheng, Muhua; Lü, Linyuan; Zhao, Ming

    2013-07-01

    Some epidemic spreading models are usually applied to analyze the propagation of opinions or news. However, the dynamics of epidemic spreading and information or behavior spreading are essentially different in many aspects. Centola's experiments [Science 329, 1194 (2010)] on behavior spreading in online social networks showed that the spreading is faster and broader in regular networks than in random networks. This result contradicts with the former understanding that random networks are preferable for spreading than regular networks. To describe the spreading in online social networks, a unknown-known-approved-exhausted four-status model was proposed, which emphasizes the effect of social reinforcement and assumes that the redundant signals can improve the probability of approval (i.e., the spreading rate). Performing the model on regular and random networks, it is found that our model can well explain the results of Centola's experiments on behavior spreading and some former studies on information spreading in different parameter space. The effects of average degree and network size on behavior spreading process are further analyzed. The results again show the importance of social reinforcement and are accordant with Centola's anticipation that increasing the network size or decreasing the average degree will enlarge the difference of the density of final approved nodes between regular and random networks. Our work complements the former studies on spreading dynamics, especially the spreading in online social networks where the information usually requires individuals' confirmations before being transmitted to others.

  12. The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

    Directory of Open Access Journals (Sweden)

    Go Myong-Hyun

    2011-07-01

    Full Text Available Abstract Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability. Please see related article BMC Medicine, 2011, 9:87

  13. The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

    Science.gov (United States)

    Blower, Sally; Go, Myong-Hyun

    2011-07-19

    Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability.

  14. Seven Deadliest Social Network Attacks

    CERN Document Server

    Timm, Carl

    2010-01-01

    Do you need to keep up with the latest hacks, attacks, and exploits effecting social networks? Then you need Seven Deadliest Social Network Attacks. This book pinpoints the most dangerous hacks and exploits specific to social networks like Facebook, Twitter, and MySpace, laying out the anatomy of these attacks including how to make your system more secure. You will discover the best ways to defend against these vicious hacks with step-by-step instruction and learn techniques to make your computer and network impenetrable. Attacks detailed in this book include: Social Networking Infrastruct

  15. Social Network Gaming Trends

    Directory of Open Access Journals (Sweden)

    Michael Gathwright

    2010-01-01

    Full Text Available The purpose of this project was to determine how long the social network game Scratch-Offs, created by game development company Spice Rack Media, will remain financially viable. The game Scratch-Offs is a freeware game (users pay nothing for the actual software and is funded through micro transactions (users must pay small amounts of money to play actual games. This implies a relationship between total games played and revenue earned. Using data provided by Spice Rack, we were able to develop an exponential equation that accurately depicts usage trends over time. This equation was used to determine the date Scratch-Offs will no longer be profitable.

  16. Elgg 18 Social Networking

    CERN Document Server

    Costello, Cash

    2012-01-01

    This book provides more than just a step-by-step guide to installing and using Elgg. It includes practical advice gained through experience on what it takes to deploy and maintain an Elgg-based site. If you are a software developer or are familiar with PHP, it provides both a tutorial-based introduction and a quick reference guide so that you can quickly extend and customize Elgg. If you want to create a social networking site using Elgg and do not have a background in software development, this book provides all the information and advice that you need written just for you. If you are a devel

  17. Social Networks and Technology Adoption

    OpenAIRE

    Hogset, Heidi

    2005-01-01

    This study analyzes social network effects on Kenyan smallholders' decision to adopt improved natural resource management techniques. These effects are decomposed into effects from social influence and learning through networks (strong ties), group effects, weak ties effects, informal finance, and conflicts arising from technological externalities, controlling for non-network effects.

  18. Underage Children and Social Networking

    Science.gov (United States)

    Weeden, Shalynn; Cooke, Bethany; McVey, Michael

    2013-01-01

    Despite minimum age requirements for joining popular social networking services such as Facebook, many students misrepresent their real ages and join as active participants in the networks. This descriptive study examines the use of social networking services (SNSs) by children under the age of 13. The researchers surveyed a sample of 199…

  19. Parameterizing Bayesian network Representations of Social-Behavioral Models by Expert Elicitation

    Energy Technology Data Exchange (ETDEWEB)

    Walsh, Stephen J.; Dalton, Angela C.; Whitney, Paul D.; White, Amanda M.

    2010-05-23

    Bayesian networks provide a general framework with which to model many natural phenomena. The mathematical nature of Bayesian networks enables a plethora of model validation and calibration techniques: e.g parameter estimation, goodness of fit tests, and diagnostic checking of the model assumptions. However, they are not free of shortcomings. Parameter estimation from relevant extant data is a common approach to calibrating the model parameters. In practice it is not uncommon to find oneself lacking adequate data to reliably estimate all model parameters. In this paper we present the early development of a novel application of conjoint analysis as a method for eliciting and modeling expert opinions and using the results in a methodology for calibrating the parameters of a Bayesian network.

  20. Opinion evolution in different social acquaintance networks.

    Science.gov (United States)

    Chen, Xi; Zhang, Xiao; Wu, Zhan; Wang, Hongwei; Wang, Guohua; Li, Wei

    2017-11-01

    Social acquaintance networks influenced by social culture and social policy have a great impact on public opinion evolution in daily life. Based on the differences between socio-culture and social policy, three different social acquaintance networks (kinship-priority acquaintance network, independence-priority acquaintance network, and hybrid acquaintance network) incorporating heredity proportion p h and variation proportion p v are proposed in this paper. Numerical experiments are conducted to investigate network topology and different phenomena during opinion evolution, using the Deffuant model. We found that in kinship-priority acquaintance networks, similar to the Chinese traditional acquaintance networks, opinions always achieve fragmentation, resulting in the formation of multiple large clusters and many small clusters due to the fact that individuals believe more in their relatives and live in a relatively closed environment. In independence-priority acquaintance networks, similar to Western acquaintance networks, the results are similar to those in the kinship-priority acquaintance network. In hybrid acquaintance networks, similar to the Chinese modern acquaintance networks, only a few clusters are formed indicating that in modern China, opinions are more likely to reach consensus on a large scale. These results are similar to the opinion evolution phenomena in modern society, proving the rationality and applicability of network models combined with social culture and policy. We also found a threshold curve p v +2p h =2.05 in the results for the final opinion clusters and evolution time. Above the threshold curve, opinions could easily reach consensus. Based on the above experimental results, a culture-policy-driven mechanism for the opinion dynamic is worth promoting in this paper, that is, opinion dynamics can be driven by different social cultures and policies through the influence of heredity and variation in interpersonal relationship networks. This

  1. Opinion evolution in different social acquaintance networks

    Science.gov (United States)

    Chen, Xi; Zhang, Xiao; Wu, Zhan; Wang, Hongwei; Wang, Guohua; Li, Wei

    2017-11-01

    Social acquaintance networks influenced by social culture and social policy have a great impact on public opinion evolution in daily life. Based on the differences between socio-culture and social policy, three different social acquaintance networks (kinship-priority acquaintance network, independence-priority acquaintance network, and hybrid acquaintance network) incorporating heredity proportion ph and variation proportion pv are proposed in this paper. Numerical experiments are conducted to investigate network topology and different phenomena during opinion evolution, using the Deffuant model. We found that in kinship-priority acquaintance networks, similar to the Chinese traditional acquaintance networks, opinions always achieve fragmentation, resulting in the formation of multiple large clusters and many small clusters due to the fact that individuals believe more in their relatives and live in a relatively closed environment. In independence-priority acquaintance networks, similar to Western acquaintance networks, the results are similar to those in the kinship-priority acquaintance network. In hybrid acquaintance networks, similar to the Chinese modern acquaintance networks, only a few clusters are formed indicating that in modern China, opinions are more likely to reach consensus on a large scale. These results are similar to the opinion evolution phenomena in modern society, proving the rationality and applicability of network models combined with social culture and policy. We also found a threshold curve pv+2 ph=2.05 in the results for the final opinion clusters and evolution time. Above the threshold curve, opinions could easily reach consensus. Based on the above experimental results, a culture-policy-driven mechanism for the opinion dynamic is worth promoting in this paper, that is, opinion dynamics can be driven by different social cultures and policies through the influence of heredity and variation in interpersonal relationship networks. This

  2. Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models

    Directory of Open Access Journals (Sweden)

    Juhwan Kim

    2018-01-01

    Full Text Available Recent developments in artificial intelligence (AI have led to a significant increase in the use of AI technologies. Many experts are researching and developing AI technologies in their respective fields, often submitting papers and patent applications as a result. In particular, owing to the characteristics of the patent system that is used to protect the exclusive rights to registered technology, patent documents contain detailed information on the developed technology. Therefore, in this study, we propose a statistical method for analyzing patent data on AI technology to improve our understanding of sustainable technology in the field of AI. We collect patent documents that are related to AI technology, and then analyze the patent data to identify sustainable AI technology. In our analysis, we develop a statistical method that combines social network analysis and Bayesian modeling. Based on the results of the proposed method, we provide a technological structure that can be applied to understand the sustainability of AI technology. To show how the proposed method can be applied to a practical problem, we apply the technological structure to a case study in order to analyze sustainable AI technology.

  3. Predicting the evolution of social networks with life cycle events

    NARCIS (Netherlands)

    Sharmeen, F.; Arentze, T.A.; Timmermans, H.J.P.

    2015-01-01

    This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship selection to incorporate these dynamics of personal social

  4. Online networks destroy social trust

    OpenAIRE

    Sabatini, Fabio; Sarracino, Francesco

    2014-01-01

    Studies in the social capital literature have documented two stylised facts: first, a decline in measures of social participation has occurred in many OECD countries. Second, and more recently, the success of social networking sites (SNSs) has resulted in a steep rise in online social participation. Our study adds to this body of research by conducting the first empirical assessment of how online networking affects two economically relevant aspects of social capital, i.e. trust and sociabilit...

  5. An actor-based model of social network influence on adolescent body size, screen time, and playing sports.

    Directory of Open Access Journals (Sweden)

    David A Shoham

    Full Text Available Recent studies suggest that obesity may be "contagious" between individuals in social networks. Social contagion (influence, however, may not be identifiable using traditional statistical approaches because they cannot distinguish contagion from homophily (the propensity for individuals to select friends who are similar to themselves or from shared environmental influences. In this paper, we apply the stochastic actor-based model (SABM framework developed by Snijders and colleagues to data on adolescent body mass index (BMI, screen time, and playing active sports. Our primary hypothesis was that social influences on adolescent body size and related behaviors are independent of friend selection. Employing the SABM, we simultaneously modeled network dynamics (friendship selection based on homophily and structural characteristics of the network and social influence. We focused on the 2 largest schools in the National Longitudinal Study of Adolescent Health (Add Health and held the school environment constant by examining the 2 school networks separately (N = 624 and 1151. Results show support in both schools for homophily on BMI, but also for social influence on BMI. There was no evidence of homophily on screen time in either school, while only one of the schools showed homophily on playing active sports. There was, however, evidence of social influence on screen time in one of the schools, and playing active sports in both schools. These results suggest that both homophily and social influence are important in understanding patterns of adolescent obesity. Intervention efforts should take into consideration peers' influence on one another, rather than treating "high risk" adolescents in isolation.

  6. Fundamental structures of dynamic social networks

    DEFF Research Database (Denmark)

    Sekara, Vedran; Stopczynski, Arkadiusz; Jørgensen, Sune Lehmann

    2016-01-01

    Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships...... and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection......, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals...

  7. A Privacy Preservation Model for Health-Related Social Networking Sites

    OpenAIRE

    Li, Jingquan

    2015-01-01

    The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many use...

  8. Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    The original publication is available from www.springerlink.com. Sloep, P. (2009). Social Interaction in Learning Networks. In R. Koper (Ed.), Learning Network Services for Professional Development (pp 13-15). Berlin, Germany: Springer Verlag.

  9. On sampling social networking services

    OpenAIRE

    Wang, Baiyang

    2012-01-01

    This article aims at summarizing the existing methods for sampling social networking services and proposing a faster confidence interval for related sampling methods. It also includes comparisons of common network sampling techniques.

  10. Digital Social Network Mining for Topic Discovery

    Science.gov (United States)

    Moradianzadeh, Pooya; Mohi, Maryam; Sadighi Moshkenani, Mohsen

    Networked computers are expanding more and more around the world, and digital social networks becoming of great importance for many people's work and leisure. This paper mainly focused on discovering the topic of exchanging information in digital social network. In brief, our method is to use a hierarchical dictionary of related topics and words that mapped to a graph. Then, with comparing the extracted keywords from the context of social network with graph nodes, probability of relation between context and desired topics will be computed. This model can be used in many applications such as advertising, viral marketing and high-risk group detection.

  11. A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

    Directory of Open Access Journals (Sweden)

    Jorge Sá Silva

    2012-02-01

    Full Text Available As the Internet evolved, social networks (such as Facebook have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype.

  12. Online social networking for radiology.

    Science.gov (United States)

    Auffermann, William F; Chetlen, Alison L; Colucci, Andrew T; DeQuesada, Ivan M; Grajo, Joseph R; Heller, Matthew T; Nowitzki, Kristina M; Sherry, Steven J; Tillack, Allison A

    2015-01-01

    Online social networking services have changed the way we interact as a society and offer many opportunities to improve the way we practice radiology and medicine in general. This article begins with an introduction to social networking. Next, the latest advances in online social networking are reviewed, and areas where radiologists and clinicians may benefit from these new tools are discussed. This article concludes with several steps that the interested reader can take to become more involved in online social networking. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

  13. Quantum social networks

    International Nuclear Information System (INIS)

    Cabello, Adán; López-Tarrida, Antonio J; Danielsen, Lars Eirik; Portillo, José R

    2012-01-01

    We introduce a physical approach to social networks (SNs) in which each actor is characterized by a yes–no test on a physical system. This allows us to consider SNs beyond those originated by interactions based on pre-existing properties, as in a classical SN (CSN). As an example of SNs beyond CSNs, we introduce quantum SNs (QSNs) in which actor i is characterized by a test of whether or not the system is in a quantum state |ψ i 〉. We show that QSNs outperform CSNs for a certain task and some graphs. We identify the simplest of these graphs and show that graphs in which QSNs outperform CSNs are increasingly frequent as the number of vertices increases. We also discuss more general SNs and identify the simplest graphs in which QSNs cannot be outperformed. (paper)

  14. Churn in Social Networks

    Science.gov (United States)

    Karnstedt, Marcel; Hennessy, Tara; Chan, Jeffrey; Basuchowdhuri, Partha; Hayes, Conor; Strufe, Thorsten

    In the past, churn has been identified as an issue across most industry sectors. In its most general sense it refers to the rate of loss of customers from a company's customer base. There is a simple reason for the attention churn attracts: churning customers mean a loss of revenue. Emerging from business spaces like telecommunications (telcom) and broadcast providers, where churn is a major issue, it is also regarded as a crucial problem in many other businesses, such as online games creators, but also online social networks and discussion sites. Companies aim at identifying the risk of churn in its early stages, as it is usually much cheaper to retain a customer than to try to win him or her back. If this risk can be accurately predicted, marketing departments can target customers efficiently with tailored incentives to prevent them from leaving.

  15. The Power of Social Networks: A Model for Weaving the Scholarship of Teaching and Learning into Institutional Culture

    Directory of Open Access Journals (Sweden)

    Andrea L. Williams

    2013-09-01

    micro, the meso, and the macro. The authors argue that for SoTL to take root in organizational cultures, there must be 1 effective communication and dissemination of SoTL activity across all levels, 2 well established social networks and links between these levels (nodes, and 3 sustained support by senior administrationThe authors conclude by suggesting ways their model could be tested.

  16. Cluster-size entropy in the Axelrod model of social influence: Small-world networks and mass media

    Science.gov (United States)

    Gandica, Y.; Charmell, A.; Villegas-Febres, J.; Bonalde, I.

    2011-10-01

    We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy Sc, which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the Sc(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait qc and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

  17. A Social Networks in Education

    Science.gov (United States)

    Klimova, Blanka; Poulova, Petra

    2015-01-01

    At present social networks are becoming important in all areas of human activities. They are simply part and parcel of everyday life. They are mostly used for advertising, but they have already found their way into education. The future potential of social networks is high as it can be seen from their statistics on a daily, monthly or yearly…

  18. Social Networking Goes to School

    Science.gov (United States)

    Davis, Michelle R.

    2010-01-01

    Just a few years ago, social networking meant little more to educators than the headache of determining whether to penalize students for inappropriate activities captured on Facebook or MySpace. Now, teachers and students have an array of social-networking sites and tools--from Ning to VoiceThread and Second Life--to draw on for such serious uses…

  19. Risk aversion and social networks

    NARCIS (Netherlands)

    Kovářík, J.; van der Leij, M.J.

    2014-01-01

    This paper first investigates empirically the relationship between risk aversion and social network structure in a large group of undergraduate students. We find that risk aversion is strongly correlated to local network clustering, that is, the probability that one has a social tie to friends of

  20. Privacy in Online Social Networks

    NARCIS (Netherlands)

    Beye, Michael; Jeckmans, Arjan; Erkin, Zekeriya; Erkin, Zekeriya; Hartel, Pieter H.; Lagendijk, Reginald; Tang, Qiang; Abraham, A.

    Online Social Networks (OSNs) have become part of daily life for millions of users. Users building explicit networks that represent their social relationships and often share a wealth of personal information to their own benefit. The potential privacy risks of such behavior are often underestimated

  1. Dynamic social networks based on movement

    Science.gov (United States)

    Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

    2016-01-01

    Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

  2. Devising a New Model of Demand-Based Learning Integrated with Social Networks and Analyses of its Performance

    Directory of Open Access Journals (Sweden)

    Bekim Fetaji

    2018-02-01

    Full Text Available The focus of the research study is to devise a new model for demand based learning that will be integrated with social networks such as Facebook, twitter and other. The study investigates this by reviewing the published literature and realizes a case study analyses in order to analyze the new models’ analytical perspectives of practical implementation. The study focuses on analyzing demand-based learning and investigating how it can be improved by devising a specific model that incorporates social network use. Statistical analyses of the results of the questionnaire through research of the raised questions and hypothesis showed that there is a need for introducing new models in the teaching process. The originality stands on the prologue of the social login approach to an educational environment, whereas the approach is counted as a contribution of developing a demand-based web application, which aims to modernize the educational pattern of communication, introduce the social login approach, and increase the process of knowledge transfer as well as improve learners’ performance and skills. Insights and recommendations are provided, argumented and discussed.

  3. The model of microblog message diffusion based on complex social network

    Science.gov (United States)

    Zhang, Wei; Bai, Shu-Ying; Jin, Rui

    2014-05-01

    Microblog is a micromessage communication network in which users are the nodes and the followship between users are the edges. Sina Weibo is a typical case of these microblog service websites. As the enormous scale of nodes and complex links in the network, we choose a sample network crawled in Sina Weibo as the base of empirical analysis. The study starts with the analysis of its topological features, and brings in epidemiological SEIR model to explore the mode of message spreading throughout the microblog network. It is found that the network is obvious small-world and scale-free, which made it succeed in transferring messages and failed in resisting negative influence. In addition, the paper focuses on the rich nodes as they constitute a typical feature of Sina Weibo. It is also found that whether the message starts with a rich node will not account for its final coverage. Actually, the rich nodes always play the role of pivotal intermediaries who speed up the spreading and make the message known by much more people.

  4. Social networks a framework of computational intelligence

    CERN Document Server

    Chen, Shyi-Ming

    2014-01-01

    This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms.  The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling.  Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social network...

  5. Spatially Distributed Social Complex Networks

    Directory of Open Access Journals (Sweden)

    Gerald F. Frasco

    2014-01-01

    Full Text Available We propose a bare-bones stochastic model that takes into account both the geographical distribution of people within a country and their complex network of connections. The model, which is designed to give rise to a scale-free network of social connections and to visually resemble the geographical spread seen in satellite pictures of the Earth at night, gives rise to a power-law distribution for the ranking of cities by population size (but for the largest cities and reflects the notion that highly connected individuals tend to live in highly populated areas. It also yields some interesting insights regarding Gibrat’s law for the rates of city growth (by population size, in partial support of the findings in a recent analysis of real data [Rozenfeld et al., Proc. Natl. Acad. Sci. U.S.A. 105, 18702 (2008.]. The model produces a nontrivial relation between city population and city population density and a superlinear relationship between social connectivity and city population, both of which seem quite in line with real data.

  6. Spatially Distributed Social Complex Networks

    Science.gov (United States)

    Frasco, Gerald F.; Sun, Jie; Rozenfeld, Hernán D.; ben-Avraham, Daniel

    2014-01-01

    We propose a bare-bones stochastic model that takes into account both the geographical distribution of people within a country and their complex network of connections. The model, which is designed to give rise to a scale-free network of social connections and to visually resemble the geographical spread seen in satellite pictures of the Earth at night, gives rise to a power-law distribution for the ranking of cities by population size (but for the largest cities) and reflects the notion that highly connected individuals tend to live in highly populated areas. It also yields some interesting insights regarding Gibrat's law for the rates of city growth (by population size), in partial support of the findings in a recent analysis of real data [Rozenfeld et al., Proc. Natl. Acad. Sci. U.S.A. 105, 18702 (2008).]. The model produces a nontrivial relation between city population and city population density and a superlinear relationship between social connectivity and city population, both of which seem quite in line with real data.

  7. Social Network Supported Process Recommender System

    Directory of Open Access Journals (Sweden)

    Yanming Ye

    2014-01-01

    Full Text Available Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

  8. Social network supported process recommender system.

    Science.gov (United States)

    Ye, Yanming; Yin, Jianwei; Xu, Yueshen

    2014-01-01

    Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

  9. Analysing the Correlation between Social Network Analysis Measures and Performance of Students in Social Network-Based Engineering Education

    Science.gov (United States)

    Putnik, Goran; Costa, Eric; Alves, Cátia; Castro, Hélio; Varela, Leonilde; Shah, Vaibhav

    2016-01-01

    Social network-based engineering education (SNEE) is designed and implemented as a model of Education 3.0 paradigm. SNEE represents a new learning methodology, which is based on the concept of social networks and represents an extended model of project-led education. The concept of social networks was applied in the real-life experiment,…

  10. Anti-Social Networking

    Directory of Open Access Journals (Sweden)

    Chris Allen

    2014-01-01

    Full Text Available With research highlighting the growing incidence of public opposition to the building of mosques and the innovative use of social networking, especially Facebook, to disseminate and garner support for such opposition, a pilot study sought to investigate this in relation to the proposed Dudley “super mosque.” Focusing on the Facebook group Stop Dudley Super Mosque and Islamic Village, members were engaged online to explore why they opposed the mosque. Some of the emergent themes included planning and location, inclusion and public investment as well as those relating to notions of identity, heritage, otherness, and Islamification. Overt racist and Islamophobic reasons were also identified. The sense of political disconnect of members is also considered. Concluding with a contextualization of the findings within the existing body of scholarly output, in particular the building of mosques and Islamophobia, having recognized how spaces such as Facebook have potential to function as sites for research and method also, an extended methodological consideration is also included.

  11. The Social Network of Tracer Variations and O(100) Uncertain Photochemical Parameters in the Community Atmosphere Model

    Science.gov (United States)

    Lucas, D. D.; Labute, M.; Chowdhary, K.; Debusschere, B.; Cameron-Smith, P. J.

    2014-12-01

    Simulating the atmospheric cycles of ozone, methane, and other radiatively important trace gases in global climate models is computationally demanding and requires the use of 100's of photochemical parameters with uncertain values. Quantitative analysis of the effects of these uncertainties on tracer distributions, radiative forcing, and other model responses is hindered by the "curse of dimensionality." We describe efforts to overcome this curse using ensemble simulations and advanced statistical methods. Uncertainties from 95 photochemical parameters in the trop-MOZART scheme were sampled using a Monte Carlo method and propagated through 10,000 simulations of the single column version of the Community Atmosphere Model (CAM). The variance of the ensemble was represented as a network with nodes and edges, and the topology and connections in the network were analyzed using lasso regression, Bayesian compressive sensing, and centrality measures from the field of social network theory. Despite the limited sample size for this high dimensional problem, our methods determined the key sources of variation and co-variation in the ensemble and identified important clusters in the network topology. Our results can be used to better understand the flow of photochemical uncertainty in simulations using CAM and other climate models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC).

  12. Staying Safe on Social Network Sites

    Science.gov (United States)

    ... Tips Security Tip (ST06-003) Staying Safe on Social Networking Sites Original release date: January 26, 2011 | Last revised: ... so you should take certain precautions. What are social networking sites? Social networking sites, sometimes referred to as "friend- ...

  13. The Social Origins of Networks and Diffusion.

    Science.gov (United States)

    Centola, Damon

    2015-03-01

    Recent research on social contagion has demonstrated significant effects of network topology on the dynamics of diffusion. However, network topologies are not given a priori. Rather, they are patterns of relations that emerge from individual and structural features of society, such as population composition, group heterogeneity, homophily, and social consolidation. Following Blau and Schwartz, the author develops a model of social network formation that explores how social and structural constraints on tie formation generate emergent social topologies and then explores the effectiveness of these social networks for the dynamics of social diffusion. Results show that, at one extreme, high levels of consolidation can create highly balkanized communities with poor integration of shared norms and practices. As suggested by Blau and Schwartz, reducing consolidation creates more crosscutting circles and significantly improves the dynamics of social diffusion across the population. However, the author finds that further reducing consolidation creates highly intersecting social networks that fail to support the widespread diffusion of norms and practices, indicating that successful social diffusion can depend on moderate to high levels of structural consolidation.

  14. Networks in social policy problems

    CERN Document Server

    Scotti, marco

    2012-01-01

    Network science is the key to managing social communities, designing the structure of efficient organizations and planning for sustainable development. This book applies network science to contemporary social policy problems. In the first part, tools of diffusion and team design are deployed to challenges in adoption of ideas and the management of creativity. Ideas, unlike information, are generated and adopted in networks of personal ties. Chapters in the second part tackle problems of power and malfeasance in political and business organizations, where mechanisms in accessing and controlling informal networks often outweigh formal processes. The third part uses ideas from biology and physics to understand global economic and financial crises, ecological depletion and challenges to energy security. Ideal for researchers and policy makers involved in social network analysis, business strategy and economic policy, it deals with issues ranging from what makes public advisories effective to how networks influenc...

  15. Social Business Models

    Directory of Open Access Journals (Sweden)

    Maria Cristina Enache

    2015-09-01

    Full Text Available A Social Business embraces networks of people to create business value. A Social Business connects people to expertise. It enable individuals – whether customers, partners or employees – to form networks to generate new sources of innovation, foster creativity, and establish greater reach and exposure to new business opportunities. It establishes a foundational level of trust across these business networks and, thus, a willingness to openly share information. It empowers these networks with the collaborative, gaming and analytical tools needed for members to engage each other and creatively solve business challenges. A Social business strives to remove unnecessary boundaries between experts inside the company and experts in the marketplace. It embraces the tools and leadership models that support capturing knowledge and insight from many sources, allowing it to quickly sense changes in customer mood, employee sentiment or process efficiencies. It utilizes analytics and social connections inside and outside the company to solve business problems and capture new business opportunities. A Social Business leverages these social networks to speed up business, gaining real time insight to make quicker and better decisions. It gets information to customers and partners in new ways -- faster. Supported by ubiquitous access on mobile devices and new ways of connecting and working together in the Cloud and on open platforms, a Social Business turns time and location from constraints into advantages. Business is free to occur when and where it delivers the greatest value, allowing the organization to adapt quickly to the changing marketplace. We believe the most effective approach to enabling a Social Business centers around helping people discover expertise, develop social networks and capitalize on relationships.

  16. RECOMMENDER SYSTEMS IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Cleomar Valois Batista Jr

    2011-12-01

    Full Text Available The continued and diversified growth of social networks has changed the way in which users interact with them. With these changes, what once was limited to social contact is now used for exchanging ideas and opinions, creating the need for new features. Users have so much information at their fingertips that they are unable to process it by themselves; hence, the need to develop new tools. Recommender systems were developed to address this need and many techniques were used for different approaches to the problem. To make relevant recommendations, these systems use large sets of data, not taking the social network of the user into consideration. Developing a recommender system that takes into account the social network of the user is another way of tackling the problem. The purpose of this project is to use the theory of six degrees of separation (Watts 2003 amongst users of a social network to enhance existing recommender systems.

  17. SOCIAL NETWORKS AND INTERPERSONAL COMMUNICATION

    Directory of Open Access Journals (Sweden)

    Veronica GHEORGHIȚĂ

    2014-11-01

    Full Text Available Social networks visible influence people's ability to interact and communicate. Extending social circles by establishing virtual links involves a number of positive aspects such as: instant access to options for interaction, sharing of information to large communities of people, intensification of acts of communication, high levels of feedback and trust with people with whom we communicate. On the other hand, social networks adversely affects communication by decreasing the interaction face to face, by imposing superficial communications experiences, grammatical and spelling erosion of the language. Therefore, the study aims to capture the spread of social networks, their use and impact on interpersonal communication. More specifically, they look for the answer to the question: what is the nature of interpersonal communication that is found on social networking sites: personal, emotional, private or shared, informal, and public?

  18. A neighbourhood evolving network model

    International Nuclear Information System (INIS)

    Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.

    2006-01-01

    Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development

  19. Reputation Effects in Social Networks Do Not Promote Cooperation: An Experimental Test of the Raub & Weesie Model.

    Science.gov (United States)

    Corten, Rense; Rosenkranz, Stephanie; Buskens, Vincent; Cook, Karen S

    2016-01-01

    Despite the popularity of the notion that social cohesion in the form of dense social networks promotes cooperation in Prisoner's Dilemmas through reputation, very little experimental evidence for this claim exists. We address this issue by testing hypotheses from one of the few rigorous game-theoretic models on this topic, the Raub & Weesie model, in two incentivized lab experiments. In the experiments, 156 subjects played repeated two-person PDs in groups of six. In the "atomized interactions" condition, subjects were only informed about the outcomes of their own interactions, while in the "embedded" condition, subjects were informed about the outcomes of all interactions in their group, allowing for reputation effects. The design of the experiments followed the specification of the RW model as closely as possible. For those aspects of the model that had to be modified to allow practical implementation in an experiment, we present additional analyses that show that these modifications do not affect the predictions. Contrary to expectations, we do not find that cooperation is higher in the embedded condition than in the atomized interaction. Instead, our results are consistent with an interpretation of the RW model that includes random noise, or with learning models of cooperation in networks.

  20. Marketing Impact on Diffusion in Social Networks

    OpenAIRE

    Naumov, Pavel; Tao, Jia

    2016-01-01

    The paper proposes a way to add marketing into the standard threshold model of social networks. Within this framework, the paper studies logical properties of the influence relation between sets of agents in social networks. Two different forms of this relation are considered: one for promotional marketing and the other for preventive marketing. In each case a sound and complete logical system describing properties of the influence relation is proposed. Both systems could be viewed as extensi...

  1. Evolution of individual versus social learning on social networks.

    Science.gov (United States)

    Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

    2015-03-06

    A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  2. The Possibilities of Network Sociality

    Science.gov (United States)

    Willson, Michele

    Technologically networked social forms are broad, extensive and in demand. The rapid development and growth of web 2.0, or the social web, is evidence of the need and indeed hunger for social connectivity: people are searching for many and varied ways of enacting being-together. However, the ways in which we think of, research and write about network(ed) sociality are relatively recent and arguably restricted, warranting further critique and development. This article attempts to do several things: it raises questions about the types of sociality enacted in contemporary techno-society; critically explores the notion of the networked individual and the focus on the individual evident in much of the technology and sociality literature and asks questions about the place of the social in these discussions. It argues for a more well-balanced and multilevelled approach to questions of sociality in networked societies. The article starts from the position that possibilities enabled/afforded by the technologies we have in place have an effect upon the ways in which we understand being in the world together and our possible actions and futures. These possibilities are more than simply supplementary; in many ways they are transformative. The ways in which we grapple with these questions reveals as much about our understandings of sociality as it does about the technologies themselves.

  3. Semantic mining of social networks

    CERN Document Server

    Tang, Jie

    2015-01-01

    The first kinds of questions we try to answer are: What are the fundamental factors that form the different categories of social ties? How have reciprocal relationships been developed fro parasocial relationships? How do connected users further form groups? Another theme addressed in this book is the study of social influence. Social influence occurs when one's opinions, emotions, or behaviors are affected by others, intentionally or unintentionally. Considerable research has been conducted to verify the existence of social influence in various networks.

  4. Social networking policies in nursing education.

    Science.gov (United States)

    Frazier, Blake; Culley, Joan M; Hein, Laura C; Williams, Amber; Tavakoli, Abbas S

    2014-03-01

    Social networking use has increased exponentially in the past few years. A literature review related to social networking and nursing revealed a research gap between nursing practice and education. Although there was information available on the appropriate use of social networking sites, there was limited research on the use of social networking policies within nursing education. The purpose of this study was to identify current use of social media by faculty and students and a need for policies within nursing education at one institution. A survey was developed and administered to nursing students (n = 273) and nursing faculty (n = 33). Inferential statistics included χ², Fisher exact test, t test, and General Linear Model. Cronbach's α was used to assess internal consistency of social media scales. The χ² result indicates that there were associations with the group and several social media items. t Test results indicate significant differences between student and faculty for average of policies are good (P = .0127), policies and discipline (P = .0315), and policy at the study school (P = .0013). General Linear Model analyses revealed significant differences for "friend" a patient with a bond, unprofessional posts, policy, and nursing with class level. Results showed that students and faculty supported the development of a social networking policy.

  5. Social network analysis: Presenting an underused method for nursing research.

    Science.gov (United States)

    Parnell, James Michael; Robinson, Jennifer C

    2018-06-01

    This paper introduces social network analysis as a versatile method with many applications in nursing research. Social networks have been studied for years in many social science fields. The methods continue to advance but remain unknown to most nursing scholars. Discussion paper. English language and interpreted literature was searched from Ovid Healthstar, CINAHL, PubMed Central, Scopus and hard copy texts from 1965 - 2017. Social network analysis first emerged in nursing literature in 1995 and appears minimally through present day. To convey the versatility and applicability of social network analysis in nursing, hypothetical scenarios are presented. The scenarios are illustrative of three approaches to social network analysis and include key elements of social network research design. The methods of social network analysis are underused in nursing research, primarily because they are unknown to most scholars. However, there is methodological flexibility and epistemological versatility capable of supporting quantitative and qualitative research. The analytic techniques of social network analysis can add new insight into many areas of nursing inquiry, especially those influenced by cultural norms. Furthermore, visualization techniques associated with social network analysis can be used to generate new hypotheses. Social network analysis can potentially uncover findings not accessible through methods commonly used in nursing research. Social networks can be analysed based on individual-level attributes, whole networks and subgroups within networks. Computations derived from social network analysis may stand alone to answer a research question or incorporated as variables into robust statistical models. © 2018 John Wiley & Sons Ltd.

  6. The Social Life of Social Networks

    DEFF Research Database (Denmark)

    Robertson, Scott P.; Vatrapu, Ravi; Medina, Richard

    2009-01-01

    dialogues wished to send other participants. We show a strong integration of the Web 2.0 and new media technologies of social networking, online video, and blogs. Outside of video content, users tended to direct others to groups and applications within the Facebook community, but this homophilous behavior......This paper examines the linkage patterns of people who posted links on the Facebook “walls” of Barack Obama, Hillary Clinton, and John McCain over two years prior to the 2008 U.S. Presidential election. Linkage patterns indicate the destinations to which participants in these social networking...

  7. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim

    2014-12-03

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  8. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.

    2014-01-01

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  9. Online Identities and Social Networking

    Science.gov (United States)

    Maheswaran, Muthucumaru; Ali, Bader; Ozguven, Hatice; Lord, Julien

    Online identities play a critical role in the social web that is taking shape on the Internet. Despite many technical proposals for creating and managing online identities, none has received widespread acceptance. Design and implementation of online identities that are socially acceptable on the Internet remains an open problem. This chapter discusses the interplay between online identities and social networking. Online social networks (OSNs) are growing at a rapid pace and has millions of members in them. While the recent trend is to create explicit OSNs such as Facebook and MySpace, we also have implicit OSNs such as interaction graphs created by email and instant messaging services. Explicit OSNs allow users to create profiles and use them to project their identities on the web. There are many interesting identity related issues in the context of social networking including how OSNs help and hinder the definition of online identities.

  10. Measurement of Online Social Networks

    Science.gov (United States)

    Gjoka, Mina

    2010-01-01

    In recent years, the popularity of online social networks (OSN) has risen to unprecedented levels, with the most popular ones having hundreds of millions of users. This success has generated interest within the networking community and has given rise to a number of measurement and characterization studies, which provide a first step towards their…

  11. Social networks and research output

    NARCIS (Netherlands)

    Ductor, L.; Fafchamps, M.; Goyal, S.; van der Leij, M.J.

    2014-01-01

    We study how knowledge about the social network of an individual researcher - as embodied in his coauthor relations - helps us in developing a more accurate prediction of his future productivity. We find that incorporating information about coauthor networks leads to a modest improvement in the

  12. Kinship, family and social network

    Directory of Open Access Journals (Sweden)

    2000-12-01

    Full Text Available There is considerable overlap between Le Play's mid-eighteenth-century household model map and the regional TFR map of central-southern Europe in the 1980s. The author examines the overall structure of relationships involved in Le Play's typology and observes that both the stem-family and the unstable family area in the Southern Europe are marked by a small, close-knit network of strong ties, with kinship predominance. Vice versa, the social support hinges upon a network of kin in the stem-family area, upon an alliance among different kindred units in the unstable Mediterranean area. All this leads to formulating a hypothesis of a tri-partite model for Western European relationship models. How can we explain the relationship between family predominance as anthropological embedding and family collapse as demographic reaction? The author reconsiders this question in the light of Festinger's cognitive dissonance theory and Elder's 'principle of accentuation': different, regionally rooted, family and kinship patterns "react" in contact with an appropriate reagent, such as the macro-process of modernisation, generating different patterns of today's demographic behaviour.

  13. Collaborative networks: Reference modeling

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

  14. Social networks and factor markets

    DEFF Research Database (Denmark)

    Abay, Kibrom Araya; Kahsay, Goytom Abraha; Berhane, Guush

    In the absence of well-established factor markets, the role of indigenous institutions and social networks can be substantial for mobilizing factors for agricultural production. We investigate the role of an indigenous social network in Ethiopia, the iddir, in facilitating factor market...... transactions among smallholder farmers. Using detailed longitudinal household survey data and employing a difference-in-differences approach, we find that iddir membership improves households’ access to factor markets. Specifically, we find that joining an iddir network improves households’ access to land...

  15. Communication competence, social support, and depression among college students: a model of facebook and face-to-face support network influence.

    Science.gov (United States)

    Wright, Kevin B; Rosenberg, Jenny; Egbert, Nicole; Ploeger, Nicole A; Bernard, Daniel R; King, Shawn

    2013-01-01

    This study examined the influence of the social networking site Facebook and face-to-face support networks on depression among (N = 361) college students. The authors used the Relational Health Communication Competence Model as a framework for examining the influence of communication competence on social support network satisfaction and depression. Moreover, they examined the influence of interpersonal and social integrative motives as exogenous variables. On the basis of previous work, the authors propose and test a theoretical model using structural equation modeling. The results indicated empirical support for the model, with interpersonal motives predicting increased face-to-face and computer-mediated competence, increased social support satisfaction with face-to-face and Facebook support, and lower depression scores. The implications of the findings for theory, key limitations, and directions for future research are discussed.

  16. Information diffusion in structured online social networks

    Science.gov (United States)

    Li, Pei; Zhang, Yini; Qiao, Fengcai; Wang, Hui

    2015-05-01

    Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.

  17. Binary Classification Method of Social Network Users

    Directory of Open Access Journals (Sweden)

    I. A. Poryadin

    2017-01-01

    Full Text Available The subject of research is a binary classification method of social network users based on the data analysis they have placed. Relevance of the task to gain information about a person by examining the content of his/her pages in social networks is exemplified. The most common approach to its solution is a visual browsing. The order of the regional authority in our country illustrates that its using in school education is needed. The article shows restrictions on the visual browsing of pupil’s pages in social networks as a tool for the teacher and the school psychologist and justifies that a process of social network users’ data analysis should be automated. Explores publications, which describe such data acquisition, processing, and analysis methods and considers their advantages and disadvantages. The article also gives arguments to support a proposal to study the classification method of social network users. One such method is credit scoring, which is used in banks and credit institutions to assess the solvency of clients. Based on the high efficiency of the method there is a proposal for significant expansion of its using in other areas of society. The possibility to use logistic regression as the mathematical apparatus of the proposed method of binary classification has been justified. Such an approach enables taking into account the different types of data extracted from social networks. Among them: the personal user data, information about hobbies, friends, graphic and text information, behaviour characteristics. The article describes a number of existing methods of data transformation that can be applied to solve the problem. An experiment of binary gender-based classification of social network users is described. A logistic model obtained for this example includes multiple logical variables obtained by transforming the user surnames. This experiment confirms the feasibility of the proposed method. Further work is to define a system

  18. Brain networks of social comparison.

    Science.gov (United States)

    Kedia, Gayannée; Lindner, Michael; Mussweiler, Thomas; Ihssen, Niklas; Linden, David E J

    2013-03-27

    Social comparison, that is, the process of comparing oneself to other people, is a ubiquitous social cognitive mechanism; however, so far its neural correlates have remained unknown. The present study tested the hypothesis that social comparisons are supported by partly dissociated networks, depending on whether the dimension under comparison concerns a physical or a psychological attribute. We measured brain activity with functional MRI, whereas participants were comparing their own height or intelligence to that of individuals they personally know. Height comparisons were associated with higher activity in a frontoparietal network involved in spatial and numerical cognition. Conversely, intelligence comparisons recruited a network of midline areas that have been previously implicated in the attribution of mental states to oneself and others (Theory of mind). These findings suggest that social comparisons rely on diverse domain-specific mechanisms rather than on one unitary process.

  19. Unscrewing social media networks, twice

    DEFF Research Database (Denmark)

    Birkbak, Andreas

    2017-01-01

    Social media are often claimed to be an important new force in politics. One way to investigate such a claim is to follow an early call made in actor-network theory (ANT) to “unscrew” those entities that are assumed to be important and show how they are made up of heterogeneous networks of many...... different actors (Callon and Latour 1981). In this article I take steps towards unscrewing seven Facebook pages that were used to mobilize citizens for and against road pricing in Copenhagen in 2011-2012. But I encounter the difficulty that social media are already explicitly understood in Internet Studies...... that it can be combined with liberal notions of a singular public sphere (Somers 1995b; 1995a). In order to unscrew social media as a political force, I suggest that we need to work through both the assembling of social media networks and attend to corresponding reconstructions of liberal political narratives...

  20. Understanding Social Networks: Theories, Concepts, and Findings

    Science.gov (United States)

    Kadushin, Charles

    2012-01-01

    Despite the swift spread of social network concepts and their applications and the rising use of network analysis in social science, there is no book that provides a thorough general introduction for the serious reader. "Understanding Social Networks" fills that gap by explaining the big ideas that underlie the social network phenomenon.…

  1. Relationship between Social Networks Adoption and Social Intelligence

    Science.gov (United States)

    Gunduz, Semseddin

    2017-01-01

    The purpose of this study was to set forth the relationship between the individuals' states to adopt social networks and social intelligence and analyze both concepts according to various variables. Research data were collected from 1145 social network users in the online media by using the Adoption of Social Network Scale and Social Intelligence…

  2. The interaction evolution model of mass incidents with delay in a social network

    Science.gov (United States)

    Huo, Liang'an; Ma, Chenyang

    2017-10-01

    Recent years have witnessed rapid development of information technology. Today, modern media is widely used for the purpose of spreading information rapidly and widely. In particular, through micro-blog promotions, individuals tend to express their viewpoints and spread information on the internet, which could easily lead to public opinions. Moreover, government authorities also disseminate official information to guide public opinion and eliminate any incorrect conjecture. In this paper, a dynamical model with two delays is investigated to exhibit the interaction evolution between the public and official opinion fields in network mass incidents. Based on the theory of differential equations, the interaction mechanism between two public opinion fields in a micro-blog environment is analyzed. Two delays are proposed in the model to depict the response delays of public and official opinion fields. Some stable conditions are obtained, which shows that Hopf bifurcation can occur as delays cross critical values. Further, some numerical simulations are carried out to verify theoretical results. Our model indicates that there exists a golden time for government intervention, which should be emphasized given the impact of modern media and inaccurate rumors. If the government releases official information during the golden time, mass incidents on the internet can be controlled effectively.

  3. Social networks and environmental outcomes.

    Science.gov (United States)

    Barnes, Michele L; Lynham, John; Kalberg, Kolter; Leung, PingSun

    2016-06-07

    Social networks can profoundly affect human behavior, which is the primary force driving environmental change. However, empirical evidence linking microlevel social interactions to large-scale environmental outcomes has remained scarce. Here, we leverage comprehensive data on information-sharing networks among large-scale commercial tuna fishers to examine how social networks relate to shark bycatch, a global environmental issue. We demonstrate that the tendency for fishers to primarily share information within their ethnic group creates segregated networks that are strongly correlated with shark bycatch. However, some fishers share information across ethnic lines, and examinations of their bycatch rates show that network contacts are more strongly related to fishing behaviors than ethnicity. Our findings indicate that social networks are tied to actions that can directly impact marine ecosystems, and that biases toward within-group ties may impede the diffusion of sustainable behaviors. Importantly, our analysis suggests that enhanced communication channels across segregated fisher groups could have prevented the incidental catch of over 46,000 sharks between 2008 and 2012 in a single commercial fishery.

  4. Knowledge Strategies in Using Social Networks

    Directory of Open Access Journals (Sweden)

    Contantin BRĂTIANU

    2013-05-01

    Full Text Available Knowledge strategy selection is a multiple criteria decision-making (MCDM problem, and requires adequate methods to solve it appropriately. Knowledge strategies are also intrinsically linked to individuals and their ability to comprehend the world and leverage their intellectual assets to respond e!ectively to a fast changing environment. the essential features of social networking sites include but are not limited to: blogging, grouping, networking and instant messaging. Since the social networks facilitate communication and interaction among users, there is a continuous need of researches to examine what are the motives that a!ect the acceptance of usage of the social networks. This study aims at examining the role of the knowledge strategies that individuals employ in using social networks with respect to the overall objective of increasing the knowledge level. For this purpose we have used the Analytic Hierarchy Process (AHP mathematical model since it allows us a structuring of the overall objective on the main components. For the present research we considered a structure composed of three levels: L1 – the purpose of networking, L2 – strategies used to achieve that purpose, and L3 – activities needed for strategies implementation. At the upper level (L1, the main objective of a person in using social networks is to increase its knowledge level. To obtain the aforementioned objective we considered for the second level (L2 the following strategies: S1 – to learn from other persons; S2 – to make new friends; S3 – to increase the personal experience and visibility. the implementation of these strategies is realized through the following activities considered at the third hierarchy level (L3: A1– joining general social networks (e.g. Facebook, Google+, MySpace, Hi5 etc.; A2– joining professional social networks (e.g. LinkedIn etc.; A3– creating a personal blog (e.g. Blogster, Wordpress etc.; A4– joining online communities of

  5. Measuring Social Capital in Virtual Social Networks; Introducing Workable Indices

    Directory of Open Access Journals (Sweden)

    Hamid Abdollahian

    2013-12-01

    Full Text Available This paper will attempt to offer a set of indicators that together construct a model which will help to measure social capital among users of social networks. The world is now experiencing some new changes that are affecting conceptual equations in social sciences, two of which are of our concern here: 1- the concept of social capital that has opened its way into epistemological basis of social sciences, and; 2- the world has welcomed the birth and development of social networks in our daily life, affecting many aspects of social actions. There is Facebook from among a handful of social networks that has reached the threshold of international networking capacity with roughly one billion users. We will use Robert Putnam's theory of social capital alongside Frank's methodological innovation regarding measuring tools of social capital in order to create a marriage between these two as well as to address a yet more problematizing issue, i.e., how to measure social capital of the Facebook users. Accordingly the paper will focus on Facebook as the field of research and will introduce triangulation approach that we used in order to come up with the set of indicators. Participatory observation and online survey were used as constructing elements of triangulation approach so to generate the necessary data for the above purpose. At first, we used participatory observation through which 14 targeted samples were selected and whatever they had in their profile in Facebook were collected and analyzed. This analysis helped us to construct our questionnaire which was launched through Google docs. In the end, some 218 respondent returned their completed questionnaires. The final stage of analysis consisted of finding out how we can use the results to offer a new tool for measuring social capital of Facebook users. The research findings indicated that there are 10 indicators which should be put together if social capital is to be properly measured.

  6. Social networks and bronchial asthma.

    Science.gov (United States)

    D'Amato, Gennaro; Cecchi, Lorenzo; Liccardi, Gennaro; D'Amato, Maria; Stanghellini, Giovanni

    2013-02-01

    To focus on both positive and negative aspects of the interaction between asthmatic patients and the social networks, and to highlight the need of a psychological approach in some individuals to integrate pharmacological treatment is the purpose of review. There is evidence that in some asthmatic patients, the excessive use of social networks can induce depression and stress triggering bronchial obstruction, whereas in others their rational use can induce beneficial effects in terms of asthma management. The increasing asthma prevalence in developed countries seen at the end of last century has raised concern for the considerable burden of this disease on society as well as individuals. Bronchial asthma is a disease in which psychological implications play a role in increasing or in reducing the severity of bronchial obstruction. Internet and, in particular, social media are increasingly a part of daily life of both young and adult people, thus allowing virtual relationships with peers sharing similar interests and goals. Although social network users often disclose more about themselves online than they do in person, there might be a risk for adolescents and for sensitive individuals, who can be negatively influenced by an incorrect use. However, although some studies show an increased risk of depression, other observations suggest beneficial effects of social networks by enhancing communication, social connection and self-esteem.

  7. A Case Study of the Implementation of Social Models of Teaching in E-Learning: "The Social Networks in Education", Online Course of the Inter-Orthodox Centre of the Church of Greece

    Science.gov (United States)

    Komninou, Ioanna

    2018-01-01

    The development of e-learning has caused a growing interest in learning models that may have the best results. We believe that it is good practice to implement social learning models in the field of online education. In this case, the implementation of complex instruction in online training courses for teachers, on "Social Networks in…

  8. A framework for online social networking features

    Directory of Open Access Journals (Sweden)

    Mohsen Shafiei Nikabadi

    2014-06-01

    Full Text Available Social networks form a basis for maintaining social contacts, finding users with common interests, creating local content and sharing information. Recently networks have created a fundamental framework for analyzing and modeling the complex systems. Users' behavior studies and evaluates the system performance and leads to better planning and implementation of advertising policies on the web sites. Therefore, this study offers a framework for online social networks' characteristics. In terms of objective, this survey is practical descriptive. Sampling has been done among 384 of graduate students who have good experiences of membership in online social network. Confirmatory factor analysis is used to evaluate the validity of variables in research model. Characteristics of online social networks are defined based on six components and framework's indexes are analyzed through factor analysis. The reliability is calculated separately for each dimension and since they are all above 0.7, the reliability of the study can be confirmed. According to our research results, in terms of size, the number of people who apply for membership in various online social networking is an important index. In terms of individual preference to connect with, people who are relative play essential role in social network development. In terms of homogeneity variable, the number of people who visit their friends’ pages is important for measuring frequency variable. In terms of frequency, the use of entertainment and recreation services is more important index. In terms of proximity, being in the same city is a more important index and index of creating a sense of belonging and confidence is more important for measuring reciprocity variable.

  9. Networks in Social Policy Problems

    Science.gov (United States)

    Vedres, Balázs; Scotti, Marco

    2012-08-01

    1. Introduction M. Scotti and B. Vedres; Part I. Information, Collaboration, Innovation: The Creative Power of Networks: 2. Dissemination of health information within social networks C. Dhanjal, S. Blanchemanche, S. Clemençon, A. Rona-Tas and F. Rossi; 3. Scientific teams and networks change the face of knowledge creation S. Wuchty, J. Spiro, B. F. Jones and B. Uzzi; 4. Structural folds: the innovative potential of overlapping groups B. Vedres and D. Stark; 5. Team formation and performance on nanoHub: a network selection challenge in scientific communities D. Margolin, K. Ognyanova, M. Huang, Y. Huang and N. Contractor; Part II. Influence, Capture, Corruption: Networks Perspectives on Policy Institutions: 6. Modes of coordination of collective action: what actors in policy making? M. Diani; 7. Why skewed distributions of pay for executives is the cause of much grief: puzzles and few answers so far B. Kogut and J.-S. Yang; 8. Networks of institutional capture: a case of business in the State apparatus E. Lazega and L. Mounier; 9. The social and institutional structure of corruption: some typical network configurations of corruption transactions in Hungary Z. Szántó, I. J. Tóth and S. Varga; Part III. Crisis, Extinction, World System Change: Network Dynamics on a Large Scale: 10. How creative elements help the recovery of networks after crisis: lessons from biology A. Mihalik, A. S. Kaposi, I. A. Kovács, T. Nánási, R. Palotai, Á. Rák, M. S. Szalay-Beko and P. Csermely; 11. Networks and globalization policies D. R. White; 12. Network science in ecology: the structure of ecological communities and the biodiversity question A. Bodini, S. Allesina and C. Bondavalli; 13. Supply security in the European natural gas pipeline network M. Scotti and B. Vedres; 14. Conclusions and outlook A.-L. Barabási; Index.

  10. Adolescents' social network site use, peer appearance-related feedback, and body dissatisfaction: Testing a mediation model

    NARCIS (Netherlands)

    de Vries, D.A.; Peter, J.; de Graaf, H.; Nikken, P.

    Previous correlational research indicates that adolescent girls who use social network sites more frequently are more dissatisfied with their bodies. However, we know little about the causal direction of this relationship, the mechanisms underlying this relationship, and whether this relationship

  11. A social network model of supply chain management in formal and informal inter-firm engagement

    Directory of Open Access Journals (Sweden)

    Lokhman Hakim Osman

    2015-12-01

    Full Text Available Background: This research looks into the different effects of firms' network structural positions in an upstream supply network upon the firms' level of relational capital outcomes.  Previous research has largely focus on the context of decentralized network structure.  However, the supply network is a centralized network because of the existence of the focal firm.  The existence of the focal firm may influence the impact of relational capital outcomes.  Methods: The objective of this research is to determine the type of network structural positions required to obtain reasonable relational capital outcome in upstream supply network.  Results and conclusions: This study found that, network structural positions i.e. betweeness centrality contributed to firms' level of relational capital influence. In conclusion, firms, embedded in upstream supply network benefits differently in terms of relational capital through different degree of embeddedness.  Firms' resources should be re-aligned to match the benefits with the different network structural positions.

  12. Competing opinion diffusion on social networks.

    Science.gov (United States)

    Hu, Haibo

    2017-11-01

    Opinion competition is a common phenomenon in real life, such as with opinions on controversial issues or political candidates; however, modelling this competition remains largely unexplored. To bridge this gap, we propose a model of competing opinion diffusion on social networks taking into account degree-dependent fitness or persuasiveness. We study the combined influence of social networks, individual fitnesses and attributes, as well as mass media on people's opinions, and find that both social networks and mass media act as amplifiers in opinion diffusion, the amplifying effect of which can be quantitatively characterized. We analytically obtain the probability that each opinion will ultimately pervade the whole society when there are no committed people in networks, and the final proportion of each opinion at the steady state when there are committed people in networks. The results of numerical simulations show good agreement with those obtained through an analytical approach. This study provides insight into the collective influence of individual attributes, local social networks and global media on opinion diffusion, and contributes to a comprehensive understanding of competing diffusion behaviours in the real world.

  13. Synthesizing community wisdom: A model for sharing cancer-related resources through social networking and collaborative partnerships.

    Science.gov (United States)

    Weiss, Jacob B; Lorenzi, Nancy M; Lorenzi, Nancy

    2008-11-06

    Despite the availability of community-based support services, cancer patients and survivors are not aware of many of these resources. Without access to community programs, cancer survivors are at risk for lower quality of care and lower quality of life. At the same time, non-profit community organizations lack access to advanced consumer informatics applications to effectively promote awareness of their services. In addition to the current models of print and online resource guides, new community-driven informatics approaches are needed to achieve the goal of comprehensive care for cancer survivors. We present the formulation of a novel model for synthesizing a local communitys collective wisdom of cancer-related resources through a combination of online social networking technologies and real-world collaborative partnerships. This approach can improve awareness of essential, but underutilized community resources.

  14. The use of social networking services and their relationship with the big five personality model and job satisfaction in Korea.

    Science.gov (United States)

    Kim, Hyondong; Chung, Yang Woon

    2014-10-01

    Social networking services (SNSs) have been garnering attention from society due to their recent rapid growth. This study examines whether SNS use can affect the relationship between the Big Five personality model and individual job satisfaction. Based on a sample of 1,452 workers in Korea, the results of this study indicate that the Big Five personality model (extroversion, agreeableness, and neuroticism) was significantly related to individual job satisfaction. Further, SNS use moderated the relationship between extroversion and neuroticism with individual job satisfaction. Also, SNS use was found to increase job satisfaction of Korean workers who are more extroverted, while it also affected job satisfaction of Korean workers with low agreeableness. As SNS use plays an important role in the workplace, it is necessary to realize and appreciate the importance of SNSs in shaping and promoting job satisfaction of working individuals.

  15. Navigating Social Networks

    Science.gov (United States)

    Hamblin, DeAnna; Bartlett, Marilyn J.

    2013-01-01

    The authors note that when it comes to balancing free speech and schools' responsibilities, the online world is largely uncharted waters. Questions remain about the rights of both students and teachers in the world of social media. Although the lower courts have ruled that students' freedom of speech rights offer them some protection for…

  16. Trust Transitivity in Social Networks

    OpenAIRE

    Richters, Oliver; Peixoto, Tiago P.

    2011-01-01

    Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical...

  17. User Modeling for Point-of-Interest Recommendations in Location-Based Social Networks: The State of the Art

    Directory of Open Access Journals (Sweden)

    Shudong Liu

    2018-01-01

    Full Text Available The rapid growth of location-based services (LBSs has greatly enriched people’s urban lives and attracted millions of users in recent years. Location-based social networks (LBSNs allow users to check-in at a physical location and share daily tips on points of interest (POIs with their friends anytime and anywhere. Such a check-in behavior can make daily real-life experiences spread quickly through the Internet. Moreover, such check-in data in LBSNs can be fully exploited to understand the basic laws of humans’ daily movement and mobility. This paper focuses on reviewing the taxonomy of user modeling for POI recommendations through the data analysis of LBSNs. First, we briefly introduce the structure and data characteristics of LBSNs, and then we present a formalization of user modeling for POI recommendations in LBSNs. Depending on which type of LBSNs data was fully utilized in user modeling approaches for POI recommendations, we divide user modeling algorithms into four categories: pure check-in data-based user modeling, geographical information-based user modeling, spatiotemporal information-based user modeling, and geosocial information-based user modeling. Finally, summarizing the existing works, we point out the future challenges and new directions in five possible aspects.

  18. BRAND COMMUNICATION ON SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Otilia-Elena PLATON

    2015-07-01

    Full Text Available The communication represents a basic element for the marketing activity that helps companies to achieve their objectives. Building long-term relationships between brands and consumers is one of the most important objectives pursued by marketers. This involves brand communication and creating multiple connections with consumers, even in the online environment. From this point of view, social networks proved to be an effective way of linking brands and consumers online. This paper aims to present some aspects involved by the usage of social networks in brand communication by analyzing several examples of online marketing campaigns implemented on Facebook on the occasion of Valentine's Day by six different brands.

  19. Undermining and Strengthening Social Networks through Network Modification

    Science.gov (United States)

    Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

    2016-10-01

    Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.

  20. Social networks and factor markets

    DEFF Research Database (Denmark)

    Abay, Kibrom Araya; Kahsay, Goytom Abraha; Berhane, Guush

    2018-01-01

    We investigate the role of an indigenous social network in Ethiopia, the iddir, in facilitating factor market transactions among smallholder farmers. We use a detailed longitudinal household survey data and employ a fixed effects estimation to identify the effect of iddir membership on factor...... market transactions among farmers. We find that joining an iddir network improves households’ access to land, labour and credit transactions. Our findings also hint that iddir networks may crowd-out borrowing from local moneylenders (locally referred as ‘Arata Abedari’), a relatively expensive credit...

  1. Social networks user: current research

    OpenAIRE

    Agadullina E.R.

    2015-01-01

    The purpose of this article is to review current research studies focusing on the users of Facebook and their behaviors in social networks. This review is organized into two sections: 1) social-demographic characteristics (Age, Gender, Nationality); 2) personality characteristics (Neuroticism, Extraversion, Openness-to-Experience, Agreeableness, Conscientiousness, Narcissism, Self-esteem). The results showed that the information in the personal profile and online behavior are strongly connect...

  2. Social networks user: current research

    Directory of Open Access Journals (Sweden)

    Agadullina E.R.

    2015-12-01

    Full Text Available The purpose of this article is to review current research studies focusing on the users of Facebook and their behaviors in social networks. This review is organized into two sections: 1 social-demographic characteristics (Age, Gender, Nationality; 2 personality characteristics (Neuroticism, Extraversion, Openness-to-Experience, Agreeableness, Conscientiousness, Narcissism, Self-esteem. The results showed that the information in the personal profile and online behavior are strongly connected with socio-demographic and personality characteristics

  3. Socially Aware Heterogeneous Wireless Networks.

    Science.gov (United States)

    Kosmides, Pavlos; Adamopoulou, Evgenia; Demestichas, Konstantinos; Theologou, Michael; Anagnostou, Miltiades; Rouskas, Angelos

    2015-06-11

    The development of smart cities has been the epicentre of many researchers' efforts during the past decade. One of the key requirements for smart city networks is mobility and this is the reason stable, reliable and high-quality wireless communications are needed in order to connect people and devices. Most research efforts so far, have used different kinds of wireless and sensor networks, making interoperability rather difficult to accomplish in smart cities. One common solution proposed in the recent literature is the use of software defined networks (SDNs), in order to enhance interoperability among the various heterogeneous wireless networks. In addition, SDNs can take advantage of the data retrieved from available sensors and use them as part of the intelligent decision making process contacted during the resource allocation procedure. In this paper, we propose an architecture combining heterogeneous wireless networks with social networks using SDNs. Specifically, we exploit the information retrieved from location based social networks regarding users' locations and we attempt to predict areas that will be crowded by using specially-designed machine learning techniques. By recognizing possible crowded areas, we can provide mobile operators with recommendations about areas requiring datacell activation or deactivation.

  4. Development and Analyses of Privacy Management Models in Online Social Networks Based on Communication Privacy Management Theory

    Science.gov (United States)

    Lee, Ki Jung

    2013-01-01

    Online social networks (OSNs), while serving as an emerging means of communication, promote various issues of privacy. Users of OSNs encounter diverse occasions that lead to invasion of their privacy, e.g., published conversation, public revelation of their personally identifiable information, and open boundary of distinct social groups within…

  5. Social Networks and Welfare in Future Animal Management.

    Science.gov (United States)

    Koene, Paul; Ipema, Bert

    2014-03-17

    It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for management purposes. It is concluded that social networks are important to the welfare of human-managed animal species and that welfare management based on automatic recordings will become available in the near future.

  6. SOCIAL NETWORK EFFECTS ON ROMANTIC RELATIONSHIP

    Directory of Open Access Journals (Sweden)

    Fatma CAN

    2015-06-01

    Full Text Available The main objective of the study was to obtain information about social network variables in order to predict the relational commitment of married individuals and people having dating relationships. For this purpose, social network analysis has been carried out on 134 people having dating relationship and 154 married individuals and then Relationship Stability Scale, Subjective Norm Scale and Social Network Feature Survey prepared by the researcher were used. The results indicated that the approval of the closest social network member and the level of enjoyment of each other’s social network members had the best predictive value for relationship satisfaction and the investment to the relationship. The results also demonstrated that, approval of the social network had a negative impact on the level of the quality of alternatives and it showed that social networks were seen as a barrier function to have alternative relationships. Furthermore, by dividing social network members into two groups, for the dating group, the approval of the social network was the most significant variable for commitment but in the married group, the need for social network approval was not an important criteria because of having their relatioship already confirmed legally. When social network members were categorised and examined, the closest social network members did not differ by sex, but were varied in terms of relationship types. In the flirt group, one of their friends among his/her social network and their partners’ social network was specified as the closest social network member whereas in the married group, the closest social network member among his/her social network was their mother while it was their sibling among partner’s social network.

  7. Evolution of a large online social network

    International Nuclear Information System (INIS)

    Hu Haibo; Wang Xiaofan

    2009-01-01

    Although recently there are extensive research on the collaborative networks and online communities, there is very limited knowledge about the actual evolution of the online social networks (OSN). In the Letter, we study the structural evolution of a large online virtual community. We find that the scale growth of the OSN shows non-trivial S shape which may provide a proper exemplification for Bass diffusion model. We reveal that the evolutions of many network properties, such as density, clustering, heterogeneity and modularity, show non-monotone feature, and shrink phenomenon occurs for the path length and diameter of the network. Furthermore, the OSN underwent a transition from degree assortativity characteristic of collaborative networks to degree disassortativity characteristic of many OSNs. Our study has revealed the evolutionary pattern of interpersonal interactions in a specific population and provided a valuable platform for theoretical modeling and further analysis

  8. Social Networks and Political Parties in Chile

    Directory of Open Access Journals (Sweden)

    Adler Lomnitz, Larissa

    2002-09-01

    Full Text Available This paper describes the origin and evolution of two Chilean political parties (the Radical Party and the Christian Democrat Party through the analysis of the social networks that originated and composed them. The aim of this study is to propose a model of national political cultures on the basis of the structure of social networks related to power and of the symbol system, which legitimizes it. The structure of social networks, horizontal and vertical, are based on reciprocal or redistributive forms of exchange, on what is being exchanged and on the articulation between networks. In every society there are symmetrical and asymmetrical exchanges, which produce horizontal and vertical networks. These networks interact among themselves to form the social fabric. The dominance of some over others and how they combine, delineate the character of the political culture (authoritarian vs. egalitarian. Chile is a multiparty country within which there are cohorts of horizontal groups of friends, who informally exercise a central control over their members and create invisible boundaries setting them apart from others, in which leadership is under constrains. The result is both a strong presidential system based on an almost fanatic legitimacy, combined with factionalism and a strong parliamentary system.

  9. Social networks and spreading of epidemics

    Science.gov (United States)

    Trimper, Steffen; Zheng, Dafang; Brandau, Marian

    2004-05-01

    Epidemiological processes are studied within a recently proposed social network model using the susceptible-infected-refractory dynamics (SIR) of an epidemic. Within the network model, a population of individuals may be characterized by H independent hierarchies or dimensions, each of which consists of groupings of individuals into layers of subgroups. Detailed numerical simulations reveals that for H > 1, the global spreading results regardless of the degree of homophily α of the individuals forming a social circle. For H = 1, a transition from a global to a local spread occurs as the population becomes decomposed into increasingly homophilous groups. Multiple dimensions in classifying individuals (nodes) thus make a society (computer network) highly susceptible to large scale outbreaks of infectious diseases (viruses). The SIR-model can be extended by the inclusion of waiting times resulting in modified distribution function of the recovered.

  10. Privacy and Social Networking Sites

    Science.gov (United States)

    Timm, Dianne M.; Duven, Carolyn J.

    2008-01-01

    College students are relying on the Internet to make connections with other people every day. As the Internet has developed and grown, so have the capabilities for interaction. Social networking sites, a group of Web sites that provide people with the opportunity to create an online profile and to share that profile with others, are a part of…

  11. Social Networking: Keeping It Clean

    Science.gov (United States)

    Waters, John K.

    2011-01-01

    The need to maintain an unpolluted learning environment is no easy task for schools and districts that have incorporated social networking sites into their educational life. The staff and teachers at Blaine High School in Minnesota's Anoka-Hennepin District 11 had been considering the pros and cons of establishing a school Facebook page when the…

  12. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

    Software process improvement in small, agile organizations is often problematic. Model-based approaches seem to overlook problems. We have been seeking an alternative approach to overcome this through action research. Here we report on a piece of action research from which we developed an approach...... to map social networks and suggest how it can be used in software process improvement. We applied the mapping approach in a small software company to support the realization of new ways of improving software processes. The mapping approach was found useful in improving social networks, and thus furthers...... software process improvement....

  13. Origin of Peer Influence in Social Networks

    Science.gov (United States)

    Pinheiro, Flávio L.; Santos, Marta D.; Santos, Francisco C.; Pacheco, Jorge M.

    2014-03-01

    Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends' friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.

  14. Status differentiation : New insights from agent-based modeling and social network analysis

    NARCIS (Netherlands)

    Grow, André

    2016-01-01

    Status is an important aspect of social life that affects people from the day they are born until the day they die. In this dissertation, André Grow examines the processes by which status inequality can emerge between individuals and between social groups, such as men/women, whites/non-whites, and

  15. Social capital, friendship networks, and youth unemployment.

    Science.gov (United States)

    Hällsten, Martin; Edling, Christofer; Rydgren, Jens

    2017-01-01

    Youth unemployment is a contemporary social problem in many societies. Youths often have limited access to information about jobs and limited social influence, yet little is known about the relationship between social capital and unemployment risk among youth. We study the effect of social capital on unemployment risk in a sample of 19 year olds of Swedish, Iranian, and Yugoslavian origin living in Sweden (N = 1590). We distinguish between two dimensions of social capital: occupational contact networks and friendship networks. First, ego's unemployment is found to be strongly associated with friends' unemployment among individuals of Yugoslavian origins and individuals of Swedish origin, but not Iranian origin. Second, occupational contact networks reduce unemployment risks for all groups, but especially so for Iranians. The effect sizes of the two dimensions are similar and substantial: going from low to high values on these measures is associated with a difference of some 60-70 percent relative difference in unemployment risk. The findings are robust to a number of different model specifications, including a rich set of social origin controls, personality traits, educational performance, friends' characteristics, and friendship network characteristics, as well as controls for geographical employment patterns. A sensitivity simulation shows that homogeneity bias need to be very strong to explain away the effect. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Using the forest, people, fire agent-based social network model to investigate interactions in social-ecological systems

    Science.gov (United States)

    Paige Fischer; Adam Korejwa; Jennifer Koch; Thomas Spies; Christine Olsen; Eric White; Derric Jacobs

    2013-01-01

    Wildfire links social and ecological systems in dry-forest landscapes of the United States. The management of these landscapes, however, is bifurcated by two institutional cultures that have different sets of beliefs about wildfire, motivations for managing wildfire risk, and approaches to administering policy. Fire protection, preparedness, and response agencies often...

  17. SocialBrowsing: Integrating Social Networks and Web Browsing

    National Research Council Canada - National Science Library

    Golbeck, Jennifer; Wasser, Michael M

    2007-01-01

    .... The extension is paired with services provided by social networking websites, analyzes the page's contents, and adds tooltips and highlighting to indicate when there is relevant social information...

  18. Social contagions on correlated multiplex networks

    Science.gov (United States)

    Wang, Wei; Cai, Meng; Zheng, Muhua

    2018-06-01

    The existence of interlayer degree correlations has been disclosed by abundant multiplex network analysis. However, how they impose on the dynamics of social contagions are remain largely unknown. In this paper, we propose a non-Markovian social contagion model in multiplex networks with inter-layer degree correlations to delineate the behavior spreading, and develop an edge-based compartmental (EBC) theory to describe the model. We find that multiplex networks promote the final behavior adoption size. Remarkably, it can be observed that the growth pattern of the final behavior adoption size, versus the behavioral information transmission probability, changes from discontinuous to continuous once decreasing the behavior adoption threshold in one layer. We finally unravel that the inter-layer degree correlations play a role on the final behavior adoption size but have no effects on the growth pattern, which is coincidence with our prediction by using the suggested theory.

  19. Food: Transformation in Social Networks

    Directory of Open Access Journals (Sweden)

    Daria N. Karpova

    2014-01-01

    Full Text Available The modem network and digitalized society is full of social changes in various accustomed spheres of our lives including transformation in food practices. The author gives an example of the easiest way how to book food virtually and get it home this day according to tastes of a customer. Moreover the article represents new forms of specific societies existed in the Internet called food-blogs. This, on the author's mind, changes the traditional mechanism of people's choice. Food-blogs are analyzed through the prism of multifunctionalism and dynamics of food and trust. When the process of food preparing and eating attains new communicative functions. Moreover the author notes some social reasons why one user choses this or that food-blog. For instance, the popularity of blogger and network users trust, mostly «blinded». Beside the point, the conception of «trust» used in the text is based on science works of contemporary sociologist P. Sztompka. Both socialized and communicative functions of food are described through theories of R. Bart and G. Simmel. It is underlined in the text that food transforms and gains new qualities notin traditional ways we used to think but in social and cultural construction in virtual space and through network communication.

  20. Social Networking: It's Not What You Think

    Science.gov (United States)

    Jones, Kevin D.

    2010-01-01

    This slide presentation reviews some of the current uses of the social networking sites available on the internet. It list some of the skills that are now considered obsolete and reviews the major social networking sites.

  1. Social network predictors of latrine ownership.

    Science.gov (United States)

    Shakya, Holly B; Christakis, Nicholas A; Fowler, James H

    2015-01-01

    Poor sanitation, including the lack of clean functioning toilets, is a major factor contributing to morbidity and mortality from infectious diseases in the developing world. We examine correlates of latrine ownership in rural India with a focus on social network predictors. Participants from 75 villages provided the names of their social contacts as well as their own relevant demographic and household characteristics. Using these measures, we test whether the latrine ownership of an individual's social contacts is a significant predictor of individual latrine ownership. We also investigate whether network centrality significantly predicts latrine ownership, and if so, whether it moderates the relationship between the latrine ownership of the individual and that of her social contacts. Our results show that, controlling for the standard predictors of latrine ownership such as caste, education, and income, individuals are more likely to own latrines if their social contacts own latrines. Interaction models suggest that this relationship is stronger among those of the same caste, the same education, and those with stronger social ties. We also find that more central individuals are more likely to own latrines, but the correlation in latrine ownership between social contacts is strongest among individuals on the periphery of the network. Although more data is needed to determine how much the clustering of latrine ownership may be caused by social influence, the results here suggest that interventions designed to promote latrine ownership should consider focusing on those at the periphery of the network. The reason is that they are 1) less likely to own latrines and 2) more likely to exhibit the same behavior as their social contacts, possibly as a result of the spread of latrine adoption from one person to another. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Social power and opinion formation in complex networks

    Science.gov (United States)

    Jalili, Mahdi

    2013-02-01

    In this paper we investigate the effects of social power on the evolution of opinions in model networks as well as in a number of real social networks. A continuous opinion formation model is considered and the analysis is performed through numerical simulation. Social power is given to a proportion of agents selected either randomly or based on their degrees. As artificial network structures, we consider scale-free networks constructed through preferential attachment and Watts-Strogatz networks. Numerical simulations show that scale-free networks with degree-based social power on the hub nodes have an optimal case where the largest number of the nodes reaches a consensus. However, given power to a random selection of nodes could not improve consensus properties. Introducing social power in Watts-Strogatz networks could not significantly change the consensus profile.

  3. Social Network Analysis and informal trade

    DEFF Research Database (Denmark)

    Walther, Olivier

    networks can be applied to better understand informal trade in developing countries, with a particular focus on Africa. The paper starts by discussing some of the fundamental concepts developed by social network analysis. Through a number of case studies, we show how social network analysis can...... illuminate the relevant causes of social patterns, the impact of social ties on economic performance, the diffusion of resources and information, and the exercise of power. The paper then examines some of the methodological challenges of social network analysis and how it can be combined with other...... approaches. The paper finally highlights some of the applications of social network analysis and their implications for trade policies....

  4. Social networking services: technologies and applications

    OpenAIRE

    Puzyrnyy, Oleksandr

    2011-01-01

    Puzyrnyy, Oleksandr. 2011. Social networking services: technologies and applications. Bachelor's Thesis. Kemi-Tornio University of Applied Sciences. Business and Culture. Pages 52. The aim of this thesis is to describe the concept of social networking, its technological base, business opportunities and future perspectives. The study discovers how social networks are made and which different purposes they might have. In addition, social networking is viewed as a part of business strategy o...

  5. Social networks and cooperation: a bibliometric study

    Directory of Open Access Journals (Sweden)

    Ana Paula Lopes

    2013-05-01

    Full Text Available The social network analysis involves social and behavioral science. The decentralization of productive activities, such as the formation of "network organizations" as a result of downsizing of large corporate structures of the past, marked by outsoucing and formation of alliances, shows the importance of this theme. The main objective of this paper is to analyze the theory of cooperation and social networks over a period of 24 years. For this, was performed a bibliometric study with content analysis. The database chosen for the initial sample search was ISI Web of Science. The search topics were “social network” and “cooperation”. Were analyzed 97 articles and their references, through networks of citations. The main identified research groups dealing with issues related to trust, strategic alliances, natural cooperation, game theory, social capital, intensity of interaction, reciprocity and innovation. It was found that the publications occurred in a large number of journals, which indicates that the theme is multidisciplinary, and only five journals published at least three articles. Although the first publication has occurred in 1987, was from 2006 that the publications effectively increased. The areas most related to the theme of the research were performance, evolution, management, graphics, model and game theory.

  6. When business networks “kill” social networks

    DEFF Research Database (Denmark)

    Jackson, Laurel; Young, L.

    2016-01-01

    that considers the changes to a community's social network and the associated norms emerging from the growing influence of a microfinance providers' network. A case study reports the impact of microfinance on a particular Bangladesh rural community. We show there is a breakdown in traditional social networks...... in this and other poor rural villages brought about by the taking of micro loans when the families have no means of paying them back. This increased indebtedness to NGOs is perpetuating their poverty and diminishing the community's quality of life including their traditions of bounded solidarity, where families...... in the economic structure of rural Bangladesh and changing norms, in particular the changes to traditional forms of financial exchange and associated support and risk management. We conclude that public policy and a different business model that is more accountable and altruistic are needed to guide...

  7. Performance evaluation in competence-based learning model in higher education scenarios using social network: a case study

    Directory of Open Access Journals (Sweden)

    Katherina Edith GALLARDO CÓRDOVA

    2017-12-01

    Full Text Available A research about performance evaluation was conducted in a graduate online course designed in the Based-Competency Model. Facebook was used as a social and interactive tool that would permit sharing information to illustrate various aspects of diverse educational contexts as well as the impacts of the implementation of improvement projects seen from the beneficiaries’ perspective. Case Study was the methodology selected. Postgraduate students got the task to work on certain improvements on learning assessment matters. The educational scenarios were located in Mexico and Colombia. 7 units of analysis were chosen among 34 possible. The findings pointed out that students worked on their contexts in alignment with the stipulated academic competencies. The use of video materials posted and shared using Facebook allowed get a deeper understanding of the way the benefits influenced in each of the educational communities. Besides, these products evidenced students’ appropriate performance. In conclusion, the use of social networks for fortifying performance assessment is highly recommended. Moreover, it is expected that these benefits also influence some of the curricular and instructional design aspects.

  8. Nuevos modelos de comunicación, perfiles y tendencias en las redes sociales New Models of Communication, Profiles and Trends in Social Networks

    Directory of Open Access Journals (Sweden)

    Jesús Miguel Flores Vivar

    2009-10-01

    Full Text Available Las redes sociales en línea se han convertido en el estandarte de la Web 2.0, entorno que también aglutina a los blogs, wikis y chats. Existe una fina división entre una red social, un blog y un wiki. Hablar de redes sociales es referirnos al siguiente estadio de Internet, como en su momento fueron los blogs. Se han constituido en un fenómeno de masas cada vez más importante tanto así que ya algunas están integrando plataformas de blogs y wikis en una sola interfaz. Pero, ¿qué nuevas formas de comunicación y de negocio subyacen en las redes?, ¿qué perfiles profesionales se necesitan para esta nueva audiencia?, ¿deben los medios crear redes o adaptarse a los nuevos entornos de donde emerge un nuevo periodismo basado en la participación? El presente artículo intenta responder a estas y otras variables. Social networks have become the banner of Web 2.0, which also hosts blogs, wikis and chats. There is a slight dividing line between a social network, a blog and a wiki. Talking about social networks means referring to the next stage of the Internet, as talking about blogs once did. Internet social networks have become an increasingly important phenomenon because some platforms are integrating blogs and wikis on a single interface. But we could ask what new types of communication and business lie beneath these networks; what professional profiles are needed for this new audience. Should media create the networks, or just adapt to the new environments, whence a new journalism based on participation emerges? This paper tries to answer these and other questions.

  9. Social Trust Prediction Using Heterogeneous Networks

    Science.gov (United States)

    HUANG, JIN; NIE, FEIPING; HUANG, HENG; TU, YI-CHENG; LEI, YU

    2014-01-01

    Along with increasing popularity of social websites, online users rely more on the trustworthiness information to make decisions, extract and filter information, and tag and build connections with other users. However, such social network data often suffer from severe data sparsity and are not able to provide users with enough information. Therefore, trust prediction has emerged as an important topic in social network research. Traditional approaches are primarily based on exploring trust graph topology itself. However, research in sociology and our life experience suggest that people who are in the same social circle often exhibit similar behaviors and tastes. To take advantage of the ancillary information for trust prediction, the challenge then becomes what to transfer and how to transfer. In this article, we address this problem by aggregating heterogeneous social networks and propose a novel joint social networks mining (JSNM) method. Our new joint learning model explores the user-group-level similarity between correlated graphs and simultaneously learns the individual graph structure; therefore, the shared structures and patterns from multiple social networks can be utilized to enhance the prediction tasks. As a result, we not only improve the trust prediction in the target graph but also facilitate other information retrieval tasks in the auxiliary graphs. To optimize the proposed objective function, we use the alternative technique to break down the objective function into several manageable subproblems. We further introduce the auxiliary function to solve the optimization problems with rigorously proved convergence. The extensive experiments have been conducted on both synthetic and real- world data. All empirical results demonstrate the effectiveness of our method. PMID:24729776

  10. Organizational Application of Social Networking Information Technologies

    Science.gov (United States)

    Reppert, Jeffrey R.

    2012-01-01

    The focus of this qualitative research study using the Delphi method is to provide a framework for leaders to develop their own social networks. By exploring concerns in four areas, leaders may be able to better plan, implement, and manage social networking systems in organizations. The areas addressed are: (a) social networking using…

  11. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    Science.gov (United States)

    Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  12. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    Directory of Open Access Journals (Sweden)

    Mauricio Herrera

    Full Text Available There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  13. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks

    Science.gov (United States)

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions. PMID:26505473

  14. Social Networks and Students' Orthography

    Directory of Open Access Journals (Sweden)

    E. Azizovic

    2017-12-01

    Full Text Available The paper studied spelling and technical errors of students on social networks (facebook, twitter, e-mail. Social networks have over the last decade become the primary means of communication, which have more than ever made real the idea of "one world - one village". Their usage is in the most part based on language, i.e. on the writing itself and reading of the same as its most complex parts. New aspects of the use of writing, which exclude handwriting, are already using some new writing platform, such as keyboards, smart - touch surfaces, etc., provide new opportunities for redefining, as well as challenges for the writings. This paper aims to give a modest contribution in this direction.

  15. Consumer Activities and Reactions to Social Network Marketing

    OpenAIRE

    Bistra Vassileva

    2017-01-01

    The purpose of this paper is to understand consumer behavioural models with respect to their reactions to social network marketing. Theoretical background is focused on online and social network usage, motivations and behaviour. The research goal is to explore consumer reactions to the exposure of social network marketing based on the following criteria: level of brand engagement, word-of-mouth (WOM) referral behaviour, and purchase intentions. Consumers are investigated ...

  16. Organ trade using social networks

    OpenAIRE

    Waleed Alrogy; Dunia Jawdat; Muhannad Alsemari; Abdulrahman Alharbi; Abdullah Alasaad; Ali H Hajeer

    2016-01-01

    Organ transplantation is recognized worldwide as an effective treatment for organ failure. However, due to the increase in the number of patients requiring a transplant, a shortage of suitable organs for transplantation has become a global problem. Human organ trade is an illegal practice of buying or selling organs and is universally sentenced. The aim of this study was to search social network for organ trade and offerings in Saudi Arabia. The study was conducted from June 22, 2015 to Febru...

  17. Discrete Opinion Dynamics on Online Social Networks

    Science.gov (United States)

    Hu, Yan-Li; Bai, Liang; Zhang, Wei-Ming

    2013-01-01

    This paper focuses on the dynamics of binary opinions {+1, -1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors' strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-affirmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors' strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks.

  18. Discrete Opinion Dynamics on Online Social Networks

    International Nuclear Information System (INIS)

    Hu Yan-Li; Bai Liang; Zhang Wei-Ming

    2013-01-01

    This paper focuses on the dynamics of binary opinions {+1, −1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors' strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-affirmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors' strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks. (general)

  19. Applications of social network analysis to obesity: a systematic review.

    Science.gov (United States)

    Zhang, S; de la Haye, K; Ji, M; An, R

    2018-04-20

    People's health behaviours and outcomes can be profoundly shaped by the social networks they are embedded in. Based on graph theory, social network analysis is a research framework for the study of social interactions and the structure of these interactions among social actors. A literature search was conducted in PubMed and Web of Science for articles published until August 2017 that applied social network analysis to examine obesity and social networks. Eight studies (three cross-sectional and five longitudinal) conducted in the US (n = 6) and Australia (n = 2) were identified. Seven focused on adolescents' and one on adults' friendship networks. They examined structural features of these networks that were associated with obesity, including degree distribution, popularity, modularity maximization and K-clique percolation. All three cross-sectional studies that used exponential random graph models found individuals with similar body weight status and/or weight-related behaviour were more likely to share a network tie than individuals with dissimilar traits. Three longitudinal studies using stochastic actor-based models found friendship network characteristics influenced change in individuals' body weight status and/or weight-related behaviour over time. Future research should focus on diverse populations and types of social networks and identifying the mechanisms by which social networks influence obesity to inform network-based interventions. © 2018 World Obesity Federation.

  20. Collective iteration behavior for online social networks

    Science.gov (United States)

    Liu, Jian-Guo; Li, Ren-De; Guo, Qiang; Zhang, Yi-Cheng

    2018-06-01

    Understanding the patterns of collective behavior in online social network (OSNs) is critical to expanding the knowledge of human behavior and tie relationship. In this paper, we investigate a specific pattern called social signature in Facebook and Wiki users' online communication behaviors, capturing the distribution of frequency of interactions between different alters over time in the ego network. The empirical results show that there are robust social signatures of interactions no matter how friends change over time, which indicates that a stable commutation pattern exists in online communication. By comparing a random null model, we find the that commutation pattern is heterogeneous between ego and alters. Furthermore, in order to regenerate the pattern of the social signature, we present a preferential interaction model, which assumes that new users intend to look for the old users with strong ties while old users have tendency to interact with new friends. The experimental results show that the presented model can reproduce the heterogeneity of social signature by adjusting 2 parameters, the number of communicating targets m and the max number of interactions n, for Facebook users, m = n = 5, for Wiki users, m = 2 and n = 8. This work helps in deeply understanding the regularity of social signature.

  1. Social support and social network as intermediary social determinants of dental caries in adolescents.

    Science.gov (United States)

    Fontanini, Humberto; Marshman, Zoe; Vettore, Mario

    2015-04-01

    The aim of this study was to investigate the association between intermediary social determinants, namely social support and social network with dental caries in adolescents. An adapted version of the WHO social determinants of health conceptual framework was used to organize structural and intermediary social determinants of dental caries into six blocks including perceived social support and number of social networks. A cross-sectional study was conducted with a representative sample of 542 students between 12 and 14 years of age in public schools located in the city of Dourados, Brazil in 2012. The outcome variables were caries experience (DMFT ≥ 1) and current dental caries (component D of DMFT ≥ 1) recorded by a calibrated dentist. Individual interviews were performed to collect data on perceived social support and numbers of social networks from family and friends and covariates. Multivariate Poisson regressions using hierarchical models were conducted. The prevalence of adolescents with caries experience and current dental caries was 55.2% and 32.1%, respectively. Adolescents with low numbers of social networks and low levels of social support from family (PR 1.47; 95% CI = 1.01-2.14) were more likely to have DMFT ≥ 1. Current dental caries was associated with low numbers of social networks and low levels of social support from family (PR 2.26; 95% CI = 1.15-4.44). Social support and social network were influential psychosocial factors to dental caries in adolescents. This finding requires confirmation in other countries but potentially has implications for programmes to promote oral health. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Gender differences in social networks

    Directory of Open Access Journals (Sweden)

    Komaromi Bojana

    2014-01-01

    Full Text Available This paper examines gender differences in different types of social networks. One of the main concepts relevant for studying gender differences is homophily, which refers to the tendency of people to interact more with similar individuals. In this paper homophily is analysed within the structural perspective which explains that the structures of our networks depend primarily on opportunities for social interactions, i.e. the composition and dynamics of the social context in which these interactions are embedded. Homophily is evident among males and females as early as in childhood, only to be even more prominent in school and adult years. Sex segregation is probably the most evident in the organisational context, where it has detrimental effects on women's careers, as women are generally underrepresented in positions of power and authority. Research in the last two decades pointed to the facts: 1 that men and women have very different types of organisational networks, 2 that successful men and women adopt different strategies to reach similar career objectives and acquire similar resources, and 3 that organisations also need to be actively involved in solving these gender-related issues.

  3. Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis

    Directory of Open Access Journals (Sweden)

    Diego Díaz Córdova

    2016-12-01

    Full Text Available En este artículo presentamos dos modalidades metodológicas que aún no han sido muy utilizadas en la antropología alimentaria. Por un lado, nos referimos al análisis de redes sociales y, por otro, a los modelos basados en agentes. Para ilustrar los métodos, tomaremos dos casos de materiales clásicos de la antropología alimentaria. Para el primero usaremos los platos de comida de un relevamiento hecho en la Quebrada de Humahuaca (provincia de Jujuy, Argentina y, para el segundo, utilizaremos algunos elementos del concepto aplicado por Aguirre de “estrategias domésticas de consumo”. La idea subyacente es que, dado que la alimentación se reconoce como un “hecho social total” y, por lo tanto, como un fenómeno complejo, el abordaje metodológico debe seguir necesariamente esa misma característica. Mientras más métodos utilicemos (con el grado de rigor adecuado mejor estaremos preparados para comprender la dinámica alimentaria en el medio social.

  4. From Offline Social Networks to Online Social Networks: Changes in Entrepreneurship

    Directory of Open Access Journals (Sweden)

    Yang SONG

    2015-01-01

    Full Text Available The paper reviewed studies of entrepreneurship based on the emergency of online social networks. Similar to offline social networks, entrepreneurs’ online social networks have their own unique characteristics. We first reviewed the offline network based research on entrepreneurship. Then we reviewed the studies of entrepreneurship in the context of online social networks including those focusing on topics of network structures and network ties. We highlighted online network communities based on the data collected from LinkedIn, Facebook and Twitter. Our research implies that both researcher and entrepreneurs are facing new opportunities due to the emergence of online social networks.

  5. Modeling Network Interdiction Tasks

    Science.gov (United States)

    2015-09-17

    118 xiii Table Page 36 Computation times for weighted, 100-node random networks for GAND Approach testing in Python ...in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 38 Accuracy measures for weighted, 100-node random networks for GAND...networks [15:p. 1]. A common approach to modeling network interdiction is to formulate the problem in terms of a two-stage strategic game between two

  6. The Influence of Recognition and Social Support on European Health Professionals' Occupational Stress: A Demands-Control-Social Support-Recognition Bayesian Network Model.

    Science.gov (United States)

    García-Herrero, Susana; Lopez-Garcia, Jose R; Herrera, Sixto; Fontaneda, Ignacio; Báscones, Sonia Muñoz; Mariscal, Miguel A

    2017-01-01

    Healthcare professionals undergo high levels of occupational stress as a result of their working conditions. Thus, the aim of this study is to develop a model that focuses on healthcare professionals so as to analyze the influence that job demands, control, social support, and recognition have on the likelihood that a worker will experience stress. The data collected correspond to 2,211 healthcare workers from 35 countries, as reported in the sixth European Working Condition Survey (EWCS). The results obtained from this study allow us to infer stress under several working condition scenarios and to identify the more relevant variables in order to reduce this stress in healthcare professionals, which is of paramount importance to managing the stress of workers in this sector. The Bayesian network proposed indicates that emotional demands have a greater influence on raising the likelihood of stress due to workload than do family demands. The results show that the support of colleagues, in general, has less effect on reducing stress than social support from superiors. Furthermore, the sensitivity analysis shows that, in high-demand and low-control situations, recognition clearly impacts stress, drastically reducing it.

  7. An Exploration of Social Networking Sites (SNS) Adoption in Malaysia Using Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) And Intrinsic Motivation

    OpenAIRE

    Goh Say Leng; Suddin Lada; Mohd Zulkifli Muhammad; Ag Asri Hj Ag Ibrahim; Tamrin Amboala

    2011-01-01

    The objective of the paper is to explore the factors that encourage students to adopt social network sites (SNS) in Malaysia and to use the study’s findings to develop guidelines for SNS providers on how to maximize the rate of adoption. A conceptual model of Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB) and intrinsic motivation is proposed and empirically tested in the context of SNS usage. Structural Equation modelling was used on the survey data from 283 university s...

  8. Handbook of social network technologies and applications

    CERN Document Server

    Furht, Borko

    2010-01-01

    Social networking is a concept that has existed for a long time; however, with the explosion of the Internet, social networking has become a tool for people to connect and communicate in ways that were impossible in the past. The recent development of Web 2.0 has provided many new applications, such as Myspace, Facebook, and LinkedIn. The purpose of ""Handbook of Social Networks: Technologies and Applications"" is to provide comprehensive guidelines on the current and future trends in social network technologies and applications in the field of Web-based Social Networks. This handbook includes

  9. Investigation of Social Studies Teachers' Intended Uses of Social Networks in Terms of Various Variables

    Science.gov (United States)

    Akgün, Ismail Hakan

    2016-01-01

    The aim of this research is to determine Social Studies teacher candidates' intended uses of social networks in terms of various variables. The research was carried out by using screening model of quantitative research methods. In the study, "The Social Network Intended Use Scale" was used as a data collection tool. As a result of the…

  10. Networking, or What the Social Means in Social Media

    OpenAIRE

    Taina Bucher

    2015-01-01

    This article questions the meaning of the social in social media. It does this by revisiting boyd and Ellison’s seminal paper and definition of social network sites. The article argues that social media are not so much about articulating or making an existing network visible. Rather, being social in the context of social media simply means creating connections within the boundaries of adaptive algorithmic architectures. Every click, share, like, and post creates a connection, initiates a rela...

  11. Using Social Network Research in HRM

    DEFF Research Database (Denmark)

    Kaše, Robert; King, Zella; Minbaeva, Dana

    2013-01-01

    ; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.......The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others...

  12. Online networks, social interaction and segregation: An evolutionary approach

    OpenAIRE

    Antoci, Angelo; Sabatini, Fabio

    2018-01-01

    There is growing evidence that face-to-face interaction is declining in many countries, exacerbating the phenomenon of social isolation. On the other hand, social interaction through online networking sites is steeply rising. To analyze these societal dynamics, we have built an evolutionary game model in which agents can choose between three strategies of social participation: 1) interaction via both online social networks and face-to-face encounters; 2) interaction by exclusive means of face...

  13. Dimensionality of social networks using motifs and eigenvalues.

    Directory of Open Access Journals (Sweden)

    Anthony Bonato

    Full Text Available We consider the dimensionality of social networks, and develop experiments aimed at predicting that dimension. We find that a social network model with nodes and links sampled from an m-dimensional metric space with power-law distributed influence regions best fits samples from real-world networks when m scales logarithmically with the number of nodes of the network. This supports a logarithmic dimension hypothesis, and we provide evidence with two different social networks, Facebook and LinkedIn. Further, we employ two different methods for confirming the hypothesis: the first uses the distribution of motif counts, and the second exploits the eigenvalue distribution.

  14. Recent developments in exponential random graph (p*) models for social networks

    NARCIS (Netherlands)

    Robins, Garry; Snijders, Tom; Wang, Peng; Handcock, Mark; Pattison, Philippa

    This article reviews new specifications for exponential random graph models proposed by Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handcock, M., 2006. New specifications for exponential random graph models. Sociological Methodology] and demonstrates their improvement over

  15. ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.

    Science.gov (United States)

    González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Orbegozo-Medina, Ricardo Alfredo; Pazos, Alejandro

    2014-03-24

    This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The new model is able to predict complex networks of AIDS prevalence in the US counties, taking into consideration the social determinants and activity/structure of anti-HIV drugs in preclinical assays. We trained different Artificial Neural Networks (ANNs) using as input information indices of social networks and molecular graphs. We used a Shannon information index based on the Gini coefficient to quantify the effect of income inequality in the social network. We obtained the data on AIDS prevalence and the Gini coefficient from the AIDSVu database of Emory University. We also used the Balaban information indices to quantify changes in the chemical structure of anti-HIV drugs. We obtained the data on anti-HIV drug activity and structure (SMILE codes) from the ChEMBL database. Last, we used Box-Jenkins moving average operators to quantify information about the deviations of drugs with respect to data subsets of reference (targets, organisms, experimental parameters, protocols). The best model found was a Linear Neural Network (LNN) with values of Accuracy, Specificity, and Sensitivity above 0.76 and AUROC > 0.80 in training and external validation series. This model generates a complex network of AIDS prevalence in the US at county level with respect to the preclinical activity of anti-HIV drugs in preclinical assays. To train/validate the model and predict the complex network we needed to analyze 43,249 data points including values of AIDS prevalence in 2,310 counties in the US vs ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4,856 protocols, and 10 possible experimental measures.

  16. Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

    Science.gov (United States)

    Campbell, Kenyth

    2012-01-01

    The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

  17. Understanding how social networking influences perceived satisfaction with conference experiences

    Science.gov (United States)

    van Riper, Carena J.; van Riper, Charles; Kyle, Gerard T.; Lee, Martha E.

    2013-01-01

    Social networking is a key benefit derived from participation in conferences that bind the ties of a professional community. Building social networks can lead to satisfactory experiences while furthering participants' long- and short-term career goals. Although investigations of social networking can lend insight into how to effectively engage individuals and groups within a professional cohort, this area has been largely overlooked in past research. The present study investigates the relationship between social networking and satisfaction with the 10th Biennial Conference of Research on the Colorado Plateau using structural equation modelling. Results partially support the hypothesis that three dimensions of social networking – interpersonal connections, social cohesion, and secondary associations – positively contribute to the performance of various conference attributes identified in two focus group sessions. The theoretical and applied contributions of this paper shed light on the social systems formed within professional communities and resource allocation among service providers.

  18. Social networks and employment in India

    OpenAIRE

    Tushar K. Nandi

    2010-01-01

    We investigate the influence of social networks on employment. Using data from India, we estimate the effect of caste based social networks on employment. We use a methodology that allows us to control for several omitted variable biases that often confound network effect. Our results indicate that caste based social networks are important determinant of employment in India. The implication of our findings is that a policy of positive discrimination in labour market for disadvantaged caste is...

  19. Effects of deception in social networks.

    Science.gov (United States)

    Iñiguez, Gerardo; Govezensky, Tzipe; Dunbar, Robin; Kaski, Kimmo; Barrio, Rafael A

    2014-09-07

    Honesty plays a crucial role in any situation where organisms exchange information or resources. Dishonesty can thus be expected to have damaging effects on social coherence if agents cannot trust the information or goods they receive. However, a distinction is often drawn between prosocial lies ('white' lies) and antisocial lying (i.e. deception for personal gain), with the former being considered much less destructive than the latter. We use an agent-based model to show that antisocial lying causes social networks to become increasingly fragmented. Antisocial dishonesty thus places strong constraints on the size and cohesion of social communities, providing a major hurdle that organisms have to overcome (e.g. by evolving counter-deception strategies) in order to evolve large, socially cohesive communities. In contrast, white lies can prove to be beneficial in smoothing the flow of interactions and facilitating a larger, more integrated network. Our results demonstrate that these group-level effects can arise as emergent properties of interactions at the dyadic level. The balance between prosocial and antisocial lies may set constraints on the structure of social networks, and hence the shape of society as a whole. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  20. Emergence, evolution and scaling of online social networks.

    Science.gov (United States)

    Wang, Le-Zhi; Huang, Zi-Gang; Rong, Zhi-Hai; Wang, Xiao-Fan; Lai, Ying-Cheng

    2014-01-01

    Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China) with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

  1. Emergence, evolution and scaling of online social networks.

    Directory of Open Access Journals (Sweden)

    Le-Zhi Wang

    Full Text Available Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

  2. Potential of Social Networking Sites for Distance Education Student Engagement

    Science.gov (United States)

    Lester, Jaime; Perini, Michael

    2010-01-01

    This chapter explores the potential of social networking sites for increasing student engagement for distance education learners. The authors present a modified student engagement model with a focus on the integration of technology, specifically social networking sites for community college distance education learners. The chapter concludes with…

  3. Modelling the effects of social networks on activity and travel behaviour

    NARCIS (Netherlands)

    Ronald, N.A.

    2012-01-01

    Activity-based models of transport demand are increasingly used by governments, engineering firms and consultants to predict the impact of various design and planning decisions on travel and consequently on noise emissions, energy consumption, accessibility and other performance indicators. In this

  4. Psychology and social networks: a dynamic network theory perspective.

    Science.gov (United States)

    Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

    2014-04-01

    Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

  5. Connecting Mobile Users Through Mobile Social Networks

    Directory of Open Access Journals (Sweden)

    Faisal Alkhateeb

    2012-10-01

    Full Text Available Nowadays, social networks become popular with the emerging of web-based social networking services. Recently, several mobile services are developed to connect users to their favourite social networks such as Facebook, Twitter, Flickr, etc. However, these services depends upon the existing web-based social networks. In this paper, we present a mobile service for joining groups across communities. The originality of the work is that the framework of the service allows creating and joining social networks that are self-contained for mobile company servers. The service consists of several sub-services such as users invitation, group finding and others. Users, regardless of their disability, can use the service and its sub-services without the need to create their own accounts on social web sites and thus their own groups. We also propose a privacy control policy for mobile social networks.

  6. Predicting tax avoidance by means of social network analytics

    NARCIS (Netherlands)

    Jasmien, Lismont; Cardinaels, Eddy; Bruynseels, L.M.L.; De Groote, Sander; Baesens, B.; Lemahieu, W.; Vanthienen, J.

    This study predicts tax avoidance by means of social network analytics. We extend previous literature by being the first to build a predictive model including a larger variation of network features. We construct a network of firms connected through shared board membership. Then, we apply three

  7. Egocentric Social Network Analysis of Pathological Gambling

    Science.gov (United States)

    Meisel, Matthew K.; Clifton, Allan D.; MacKillop, James; Miller, Joshua D.; Campbell, W. Keith; Goodie, Adam S.

    2012-01-01

    Aims To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family, and co-workers. is an innovative way to look at relationships among individuals; the current study was the first to our knowledge to apply SNA to gambling behaviors. Design Egocentric social network analysis was used to formally characterize the relationships between social network characteristics and gambling pathology. Setting Laboratory-based questionnaire and interview administration. Participants Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. Findings The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers, and drinkers in their social networks than did nonpathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked, and drank with than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked, and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Conclusions Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers, and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. PMID:23072641

  8. Egocentric social network analysis of pathological gambling.

    Science.gov (United States)

    Meisel, Matthew K; Clifton, Allan D; Mackillop, James; Miller, Joshua D; Campbell, W Keith; Goodie, Adam S

    2013-03-01

    To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family and co-workers is an innovative way to look at relationships among individuals; the current study was the first, to our knowledge, to apply SNA to gambling behaviors. Egocentric social network analysis was used to characterize formally the relationships between social network characteristics and gambling pathology. Laboratory-based questionnaire and interview administration. Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers and drinkers in their social networks than did non-pathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked and drank than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

  9. Consumer Activities and Reactions to Social Network Marketing

    Directory of Open Access Journals (Sweden)

    Bistra Vassileva

    2017-06-01

    Full Text Available The purpose of this paper is to understand consumer behavioural models with respect to their reactions to social network marketing. Theoretical background is focused on online and social network usage, motivations and behaviour. The research goal is to explore consumer reactions to the exposure of social network marketing based on the following criteria: level of brand engagement, word-of-mouth (WOM referral behaviour, and purchase intentions. Consumers are investigated based on their attitudes toward social network marketing and basic socio-demographic covariates using data from a sample size of 700 Bulgarian respondents (age group 21–54 years, Internet users, urban inhabitants. Factor and cluster analyses are applied. It is found that consumers are willing to receive information about brands and companies through social networks. They like to talk in social networks about these brands and companies and to share information as well (factor 2, brand engagement. Internet users are willing to share information received through social network advertising (factor 1, wom referral behaviour but they would not buy a certain brand as a result of brand communication activities in social networks (factor 3, purchase intention. Several practical implications regarding marketing activities through social networks are drawn.

  10. Will Learning Social Inclusion Assist Rural Networks

    Science.gov (United States)

    Marchant, Jillian

    2013-01-01

    Current research on social networks in some rural communities reports continuing demise despite efforts to build resilient communities. Several factors are identified as contributing to social decline including globalisation and rural social characteristics. Particular rural social characteristics, such as strong social bonds among members of…

  11. Social networks and human development / Redes sociales y desarrollo humano

    Directory of Open Access Journals (Sweden)

    Sara Gallego Trijueque

    2011-10-01

    Full Text Available The aim of this work is a brief introduction to the concept of social networks and their importance in society. Social networks have been responsible over the centuries to preserve community values, in addition to being facilitators of social interaction in human development processes, through communication and relationships between individuals.

  12. Social Media and Social Networking Applications for Teaching and Learning

    Science.gov (United States)

    Yeo, Michelle Mei Ling

    2014-01-01

    This paper aims to better understand the experiences of the youth and the educators with the tapping of social media like YouTube videos and the social networking application of Facebook for teaching and learning. This paper is interested in appropriating the benefits of leveraging of social media and networking applications like YouTube and…

  13. Social Rewards and Social Networks in the Human Brain.

    Science.gov (United States)

    Fareri, Dominic S; Delgado, Mauricio R

    2014-08-01

    The rapid development of social media and social networking sites in human society within the past decade has brought about an increased focus on the value of social relationships and being connected with others. Research suggests that we pursue socially valued or rewarding outcomes-approval, acceptance, reciprocity-as a means toward learning about others and fulfilling social needs of forming meaningful relationships. Focusing largely on recent advances in the human neuroimaging literature, we review findings highlighting the neural circuitry and processes that underlie pursuit of valued rewarding outcomes across non-social and social domains. We additionally discuss emerging human neuroimaging evidence supporting the idea that social rewards provide a gateway to establishing relationships and forming social networks. Characterizing the link between social network, brain, and behavior can potentially identify contributing factors to maladaptive influences on decision making within social situations. © The Author(s) 2014.

  14. Collective Dynamics in Physical and Social Networks

    Science.gov (United States)

    Isakov, Alexander

    We study four systems where individual units come together to display a range of collective behavior. First, we consider a physical system of phase oscillators on a network that expands the Kuramoto model to include oscillator-network interactions and the presence of noise: using a Hebbian-like learning rule, oscillators that synchronize in turn strengthen their connections to each other. We find that the average degree of connectivity strongly affects rates of flipping between aligned and anti-aligned states, and that this result persists to the case of complex networks. Turning to a fully multi-player, multi-strategy evolutionary dynamics model of cooperating bacteria that change who they give resources to and take resources from, we find several regimes that give rise to high levels of collective structure in the resulting networks. In this setting, we also explore the conditions in which an intervention that affects cooperation itself (e.g. "seeding the network with defectors") can lead to wiping out an infection. We find a non-monotonic connection between the percent of disabled cooperation and cure rate, suggesting that in some regimes a limited perturbation can lead to total population collapse. At a larger scale, we study how the locomotor system recovers after amputation in fruit flies. Through experiment and a theoretical model of multi-legged motion controlled by neural oscillators, we find that proprioception plays a role in the ability of flies to control leg forces appropriately to recover from a large initial turning bias induced by the injury. Finally, at the human scale, we consider a social network in a traditional society in Africa to understand how social ties lead to group formation for collective action (stealth raids). We identify critical and distinct roles for both leadership (important for catalyzing a group) and friendship (important for final composition). We conclude with prospects for future work.

  15. Modelling computer networks

    International Nuclear Information System (INIS)

    Max, G

    2011-01-01

    Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

  16. An evolving network model with community structure

    International Nuclear Information System (INIS)

    Li Chunguang; Maini, Philip K

    2005-01-01

    Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

  17. Social networks in cardiovascular disease management.

    Science.gov (United States)

    Shaya, Fadia T; Yan, Xia; Farshid, Maryam; Barakat, Samer; Jung, Miah; Low, Sara; Fedder, Donald

    2010-12-01

    Cardiovascular disease remains the leading cause of death in the USA. Social networks have a positive association with obesity, smoking cessation and weight loss. This article summarizes studies evaluating the impact of social networks on the management of cardiovascular disease. The 35 studies included in the article describe the impact of social networks on a decreased incidence of cardiovascular disease, depression and mortality. In addition, having a large-sized social network is also associated with better outcomes and improved health. The role of pharmacists is beginning to play an important role in the patient-centered medical home, which needs to be incorporated into social networks. The patient-centered medical home can serve as an adaptive source for social network evolvement.

  18. Social Networking Sites: A premise on enhancement

    OpenAIRE

    MANINDERPAL SINGH SAINI; GYEWON MOON

    2013-01-01

    This article address five constructs that are paramount toward continued evolution of social networking sites (SNS`s) they include, - stabilisation, visual, language, security and flexibility. These constructs add to our proposed framework. Firmly grounded research on social networking sites and literature, we propose that user feedback, is the critical component that stimulates the development and growth of social networking sites online. We offer a framework that can aid new and current soc...

  19. PRIVACY PROTECTION PROBLEMS IN SOCIAL NETWORKS

    OpenAIRE

    OKUR, M. Cudi

    2011-01-01

    Protecting privacy has become a major concern for most social network users because of increased difficulties of controlling the online data. This article presents an assessment of the common privacy related risks of social networking sites. Open and hidden privacy risks of active and passive online profiles are examined and increasing share of social networking in these phenomena is discussed. Inadequacy of available legal and institutional protection is demonstrated and the effectiveness of...

  20. The Strategic Paradox of Social Networks

    Science.gov (United States)

    2011-03-18

    United States claimed to have met online.9 And in 2010, Facebook claimed over 500 million users, which would make the social networking service the...service culture, or occupational specialty. One drawback with social networks concerns the protection of individual privacy. Facebook , for...St ra te gy R es ea rc h Pr oj ec t THE STRATEGIC PARADOX OF SOCIAL NETWORKS BY COLONEL ROBERT COTE United States Marine Corps

  1. Recruitment dynamics in adaptive social networks

    International Nuclear Information System (INIS)

    Shkarayev, Maxim S; Shaw, Leah B; Schwartz, Ira B

    2013-01-01

    We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime). (paper)

  2. Recruitment dynamics in adaptive social networks

    Science.gov (United States)

    Shkarayev, Maxim S.; Schwartz, Ira B.; Shaw, Leah B.

    2013-06-01

    We model recruitment in adaptive social networks in the presence of birth and death processes. Recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. Only a susceptible subset of nodes can be recruited. The recruiting individuals may adapt their connections in order to improve recruitment capabilities, thus changing the network structure adaptively. We derive a mean-field theory to predict the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment level, as well as on network topology. The theoretical predictions are compared with direct simulations of the full system. We identify two parameter regimes with qualitatively different bifurcation diagrams depending on whether nodes become susceptible frequently (multiple times in their lifetime) or rarely (much less than once per lifetime).

  3. Polarity related influence maximization in signed social networks.

    Directory of Open Access Journals (Sweden)

    Dong Li

    Full Text Available Influence maximization in social networks has been widely studied motivated by applications like spread of ideas or innovations in a network and viral marketing of products. Current studies focus almost exclusively on unsigned social networks containing only positive relationships (e.g. friend or trust between users. Influence maximization in signed social networks containing both positive relationships and negative relationships (e.g. foe or distrust between users is still a challenging problem that has not been studied. Thus, in this paper, we propose the polarity-related influence maximization (PRIM problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks. To address the PRIM problem, we first extend the standard Independent Cascade (IC model to the signed social networks and propose a Polarity-related Independent Cascade (named IC-P diffusion model. We prove that the influence function of the PRIM problem under the IC-P model is monotonic and submodular Thus, a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem in signed social networks. Experimental results on two signed social network datasets, Epinions and Slashdot, validate that our approximation algorithm for solving the PRIM problem outperforms state-of-the-art methods.

  4. Privacy Breach Analysis in Social Networks

    Science.gov (United States)

    Nagle, Frank

    This chapter addresses various aspects of analyzing privacy breaches in social networks. We first review literature that defines three types of privacy breaches in social networks: interactive, active, and passive. We then survey the various network anonymization schemes that have been constructed to address these privacy breaches. After exploring these breaches and anonymization schemes, we evaluate a measure for determining the level of anonymity inherent in a network graph based on its topological structure. Finally, we close by emphasizing the difficulty of anonymizing social network data while maintaining usability for research purposes and offering areas for future work.

  5. Improving Family Forest Knowledge Transfer through Social Network Analysis

    Science.gov (United States)

    Gorczyca, Erika L.; Lyons, Patrick W.; Leahy, Jessica E.; Johnson, Teresa R.; Straub, Crista L.

    2012-01-01

    To better engage Maine's family forest landowners our study used social network analysis: a computational social science method for identifying stakeholders, evaluating models of engagement, and targeting areas for enhanced partnerships. Interviews with researchers associated with a research center were conducted to identify how social network…

  6. Exploring Self-Disclosure in Online Social Networks

    Science.gov (United States)

    Velasco-Martin, Javier

    2013-01-01

    This project explores how experienced adult users of social media disclose personal information over online social networks (OSN). This work introduces a four-dimensional model to serve as a foundational framework for the study of online self-disclosure (OSD); these four dimensions are personal, social, technological and contextual, and support…

  7. Privacy and technology challenges for ubiquitous social networking

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Seet, Boon-Chong

    2015-01-01

    towards important challenges such as social sensing, enabling social networking and privacy protection. In this paper we firstly investigate the methods and technologies for acquisition of the relevant context for promotion of sociability among inhabitants of USN environments. Afterwards, we review...... architectures and techniques for enabling social interactions between participants. Finally, we identify privacy as the major challenge for networking in USN environments. Consequently, we depict design guidelines and review privacy protection models for facilitating personal information disclosure....

  8. Modeling the citation network by network cosmology.

    Science.gov (United States)

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  9. Social relations: network, support and relational strain

    DEFF Research Database (Denmark)

    Due, P; Holstein, B; Lund, Rikke

    1999-01-01

    We introduce a conceptual framework with social relations as the main concept and the structure and the function of social relations as subconcepts. The structure of social relations covers aspects of formal relations and social network. The function of social relations covers social support......,011. The postal questionnaires were answered by a random sample in each of the age groups. The results show marked age and gender differences in both the structure and the function of social relations. The social network, measured as weekly contacts, weakens with age and so does instrumental support. Emotional...... support is unrelated to this decline in contact frequency and appears to be at the same level for younger and older individuals. Relational strain, measured as conflicts, declines with age for all kinds of social relations. The weakening of the social network with age does not seem to affect the level...

  10. Animal welfare: a social networks perspective.

    Science.gov (United States)

    Kleinhappel, Tanja K; John, Elizabeth A; Pike, Thomas W; Wilkinson, Anna; Burman, Oliver H P

    2016-01-01

    Social network theory provides a useful tool to study complex social relationships in animals. The possibility to look beyond dyadic interactions by considering whole networks of social relationships allows researchers the opportunity to study social groups in more natural ways. As such, network-based analyses provide an informative way to investigate the factors influencing the social environment of group-living animals, and so has direct application to animal welfare. For example, animal groups in captivity are frequently disrupted by separations, reintroductions and/or mixing with unfamiliar individuals and this can lead to social stress and associated aggression. Social network analysis ofanimal groups can help identify the underlying causes of these socially-derived animal welfare concerns. In this review we discuss how this approach can be applied, and how it could be used to identify potential interventions and solutions in the area of animal welfare.

  11. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  12. Social networking and privacy attitudes among

    OpenAIRE

    Kristen A. Carruth; Harvey J. Ginsburg

    2014-01-01

    Daily use of social networking sites (SNS) such as Facebook has become routine for millions of Internet users. Facebook is currently still the most popular social media site. Social networking has been rapidly adopted by societies around the world. In particular, social media like Facebook provide sites where users can personalize a profile with their information, pictures, and videos that can be shared with other users. This information can be used in ways that may violate users’ privacy ...

  13. Social networks, social satisfaction and place attachment in the neighborhood

    NARCIS (Netherlands)

    Weijs - Perrée, M.; van den Berg, P.E.W.; Arentze, T.A.; Kemperman, A.D.A.M.

    2017-01-01

    Feeling socially integrated and being satisfied with one’s social life are important indicators for happiness and well-being of individuals and for the strength of local communities. The effect of the living environment on social networks and the importance of local social contacts in the

  14. Mobile Social Network in a Cultural Context

    DEFF Research Database (Denmark)

    Liu, Jun

    2010-01-01

    , and mobile phone rumours, this study observes that mobile social networks are a way that Chinese people cultivate, maintain and strengthen their guanxi networks. Embedding the reliability of guanxi, the message spreading via mobile communication always enjoys high credibility, while mutual obligation...... of mobile social network in China therefore emanate not only from Information and Communication Technologies, but also from the socio-cultural source - guanxi - deeply rooted in Chinese society.......the chapter “Mobile Social Network in a Cultural Context” examines the guanxi-embedded mobile social network in China. By focusing on three concrete case studies with 56 in-depth interviews, including New Year text message greetings, mobile social networks for job allocations among migrant workers...

  15. Mobile social networking an innovative approach

    CERN Document Server

    Zhang, Daqing

    2014-01-01

    The use of contextually aware, pervasive, distributed computing, and sensor networks to bridge the gap between the physical and online worlds is the basis of mobile social networking. This book shows how applications can be built to provide mobile social networking, the research issues that need to be solved to enable this vision, and how mobile social networking can be used to provide computational intelligence that will improve daily life. With contributions from the fields of sociology, computer science, human-computer interaction and design, this book demonstrates how mobile social networks can be inferred from users' physical interactions both with the environment and with others, as well as how users behave around them and how their behavior differs on mobile vs. traditional online social networks.

  16. Social network in patient safety: Social media visibility

    Directory of Open Access Journals (Sweden)

    Azucena Santillán García

    2011-11-01

    Full Text Available Internet social network (social media is a powerful communication tool, and its use is expanding significantly. This paper seeks to know the current state of visibility in online social networks of active citizen talking about patient safety. This is an observational cross-sectional study whose target population is the websites Facebook, Twitter and Tuenti in Spain. By three consecutive cuts social profiles were found using the searching terms “seguridad+paciente” and “safety+patient”. There were found 5 profiles on Facebook that met the search criteria, 6 on Twitter and none were found on Tuenti. It is concluded that although there is evidence of the rise of social networking, citizen network involved in patient safety appears not to be significantly represented within the social networks examined.

  17. Activity-Driven Influence Maximization in Social Networks

    DEFF Research Database (Denmark)

    Kumar, Rohit; Saleem, Muhammad Aamir; Calders, Toon

    2017-01-01

    -driven approach based on the identification of influence propagation patterns. In the first work, we identify so-called information-channels to model potential pathways for information spread, while the second work exploits how users in a location-based social network check in to locations in order to identify...... influential locations. To make our algorithms scalable, approximate versions based on sketching techniques from the data streams domain have been developed. Experiments show that in this way it is possible to efficiently find good seed sets for influence propagation in social networks.......Interaction networks consist of a static graph with a timestamped list of edges over which interaction took place. Examples of interaction networks are social networks whose users interact with each other through messages or location-based social networks where people interact by checking...

  18. Modeling Epidemic Network Failures

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2013-01-01

    This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....

  19. Social network and lifestyle in Danish adults

    DEFF Research Database (Denmark)

    Osler, Merete

    1995-01-01

    Analyzed associations between 2,987 adults' social networks and lifestyles in terms of leisure activity, smoking, and the intake of vegetables. Compared with socially integrated men, those with few social contacts or little social support were more often inactive during leisure time and did not e...... health related behaviors. (PsycINFO Database Record (c) 2012 APA, all rights reserved)...

  20. Brain and Social Networks: Fundamental Building Blocks of Human Experience.

    Science.gov (United States)

    Falk, Emily B; Bassett, Danielle S

    2017-09-01

    How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Power to Detect Intervention Effects on Ensembles of Social Networks

    Science.gov (United States)

    Sweet, Tracy M.; Junker, Brian W.

    2016-01-01

    The hierarchical network model (HNM) is a framework introduced by Sweet, Thomas, and Junker for modeling interventions and other covariate effects on ensembles of social networks, such as what would be found in randomized controlled trials in education research. In this article, we develop calculations for the power to detect an intervention…

  2. Co-evolution of social networks and continuous actor attributes

    NARCIS (Netherlands)

    Niezink, Nynke M.D.; Snijders, Tom A.B.

    2017-01-01

    Social networks and the attributes of the actors in these networks are not static; they may develop interdependently over time. The stochastic actor-oriented model allows for statistical inference on the mechanisms driving this co-evolution process. In earlier versions of this model, dynamic actor

  3. Influencing Busy People in a Social Network.

    Science.gov (United States)

    Sarkar, Kaushik; Sundaram, Hari

    2016-01-01

    We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach.

  4. Influencing Busy People in a Social Network

    Science.gov (United States)

    Sarkar, Kaushik; Sundaram, Hari

    2016-01-01

    We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach. PMID:27711127

  5. Link prediction in multiplex online social networks

    Science.gov (United States)

    Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

    2017-02-01

    Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

  6. Social network analysis and supply chain management

    Directory of Open Access Journals (Sweden)

    Raúl Rodríguez Rodríguez

    2016-01-01

    Full Text Available This paper deals with social network analysis and how it could be integrated within supply chain management from a decision-making point of view. Even though the benefits of using social analysis have are widely accepted at both academic and industry/services context, there is still a lack of solid frameworks that allow decision-makers to connect the usage and obtained results of social network analysis – mainly both information and knowledge flows and derived results- with supply chain management objectives and goals. This paper gives an overview of social network analysis, the main social network analysis metrics, supply chain performance and, finally, it identifies how future frameworks could close the gap and link the results of social network analysis with the supply chain management decision-making processes.

  7. Evolution of Cooperation in Adaptive Social Networks

    Science.gov (United States)

    Segbroeck, Sven Van; Santos, Francisco C.; Traulsen, Arne; Lenaerts, Tom; Pacheco, Jorge M.

    Humans are organized in societies, a phenomenon that would never have been possible without the evolution of cooperative behavior. Several mechanisms that foster this evolution have been unraveled over the years, with population structure as a prominent promoter of cooperation. Modern networks of exchange and cooperation are, however, becoming increasingly volatile, and less and less based on long-term stable structure. Here, we address how this change of paradigm aspects the evolution of cooperation. We discuss analytical and numerical models in which individuals can break social ties and create new ones. Interactions are modeled as two-player dilemmas of cooperation. Once a link between two individuals has formed, the productivity of this link is evaluated. Links can be broken off at different rates. This individual capacity of forming new links or severing inconvenient ones can effectively change the nature of the game. We address random formation of new links and local linking rules as well as different individual capacities to maintain social interactions. We conclude by discussing how adaptive social networks can become an important step towards more realistic models of cultural dynamics.

  8. Science, Society, and Social Networking

    Science.gov (United States)

    White, K. S.; Lohwater, T.

    2009-12-01

    The increased use of social networking is changing the way that scientific societies interact with their members and others. The American Association for the Advancement of Science (AAAS) uses a variety of online networks to engage its members and the broader scientific community. AAAS members and non-members can interact with AAAS staff and each other on AAAS sites on Facebook, YouTube, and Twitter, as well as blogs and forums on the AAAS website (www.aaas.org). These tools allow scientists to more readily become engaged in policy by providing information on current science policy topics as well as methods of involvement. For example, members and the public can comment on policy-relevant stories from Science magazine’s ScienceInsider blog, download a weekly policy podcast, receive a weekly email update of policy issues affecting the scientific community, or watch a congressional hearing from their computer. AAAS resource websites and outreach programs, including Communicating Science (www.aaas.org/communicatingscience), Working with Congress (www.aaas.org/spp/cstc/) and Science Careers (http://sciencecareers.sciencemag.org) also provide tools for scientists to become more personally engaged in communicating their findings and involved in the policy process.

  9. Trust transitivity in social networks.

    Directory of Open Access Journals (Sweden)

    Oliver Richters

    Full Text Available Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and authority-centered. We find that these scenarios lead to sharply different patterns of trust propagation, due to the segregation of authority hubs and densely-connected communities. While the authority-centered scenario is more efficient, and leads to higher average trust values, it favours weakly-connected "fringe" nodes, which are directly trusted by authorities. The community-centered scheme, on the other hand, favours nodes with intermediate in/out-degrees, in detriment of the authorities and its "fringe" peers.

  10. Trust Transitivity in Social Networks

    Science.gov (United States)

    Richters, Oliver; Peixoto, Tiago P.

    2011-01-01

    Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary in/out-degree distributions, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust) is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP) web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and authority-centered. We find that these scenarios lead to sharply different patterns of trust propagation, due to the segregation of authority hubs and densely-connected communities. While the authority-centered scenario is more efficient, and leads to higher average trust values, it favours weakly-connected “fringe” nodes, which are directly trusted by authorities. The community-centered scheme, on the other hand, favours nodes with intermediate in/out-degrees, in detriment of the authorities and its “fringe” peers. PMID:21483683

  11. Identifying and tracking dynamic processes in social networks

    Science.gov (United States)

    Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

    2006-05-01

    The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

  12. Spectral Analysis of Rich Network Topology in Social Networks

    Science.gov (United States)

    Wu, Leting

    2013-01-01

    Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

  13. Social Networks, Ethnicity, and Entrepreneurship

    OpenAIRE

    Kerr, William R.; Mandorff, Martin

    2016-01-01

    We study the relationship between ethnicity, occupational choice, and entrepreneurship. Immigrant groups in the United States cluster in specific business sectors. For example, the concentration of Korean self-employment in dry cleaners is 34 times greater than other immigrant groups, and Gujarati-speaking Indians are similarly 108 times more concentrated in managing motels. We develop a model of social interactions where non-work relationships facilitate the acquisition of sector-specific sk...

  14. SoNeUCON_{ABC}Pro: an access control model for social networks with translucent user provenance

    OpenAIRE

    González Manzano, Lorena; Slaymaker, Mark; Fuentes García Romero de Tejada, José María de; Vayenas, Dimitris

    2018-01-01

    Proceedings of: SecureComm 2017 International Workshops, ATCS and SePrIoT, Niagara Falls, ON, Canada, October 22–25, 2017 Web-Based Social Networks (WBSNs) are used by millions of people worldwide. While WBSNs provide many benefits, privacy preservation is a concern. The management of access control can help to assure data is accessed by authorized users. However, it is critical to provide sufficient flexibility so that a rich set of conditions may be imposed by users. In this paper we coi...

  15. Emotion shapes the diffusion of moralized content in social networks

    Science.gov (United States)

    Wills, Julian A.; Jost, John T.; Tucker, Joshua A.; Van Bavel, Jay J.

    2017-01-01

    Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call “moral contagion.” Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks. PMID:28652356

  16. Emotion shapes the diffusion of moralized content in social networks.

    Science.gov (United States)

    Brady, William J; Wills, Julian A; Jost, John T; Tucker, Joshua A; Van Bavel, Jay J

    2017-07-11

    Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call "moral contagion." Using a large sample of social media communications about three polarizing moral/political issues ( n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks.

  17. Rumor Diffusion in an Interests-Based Dynamic Social Network

    Directory of Open Access Journals (Sweden)

    Mingsheng Tang

    2013-01-01

    Full Text Available To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1 positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2 with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3 a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4 a network with a smaller clustering coefficient has a larger efficiency.

  18. Corporate Social Responsibility in Online Social Networks

    DEFF Research Database (Denmark)

    Horn, Christian; Brem, Alexander; Wölfl, S.

    2014-01-01

    Considering growing public awareness of social, ethical and ecological responsibility, companies have constantly been increasing their efforts in CSR communications. Social Media as tools of brand communication receive increasing attention and it is expected that the marketing sector...

  19. Using social network analysis tools in ecology : Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay

    NARCIS (Netherlands)

    Johnson, Jeffrey C.; Luczkovich, Joseph J.; Borgatti, Stephen P.; Snijders, Tom A. B.; Luczkovich, S.P.

    2009-01-01

    Ecosystem components interact in complex ways and change over time due to a variety of both internal and external influences (climate change, season cycles, human impacts). Such processes need to be modeled dynamically using appropriate statistical methods for assessing change in network structure.

  20. Competition between global and local online social networks

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2016-04-01

    The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

  1. Competition between global and local online social networks.

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2016-04-27

    The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

  2. Social Software: Participants' Experience Using Social Networking for Learning

    Science.gov (United States)

    Batchelder, Cecil W.

    2010-01-01

    Social networking tools used in learning provides instructional design with tools for transformative change in education. This study focused on defining the meanings and essences of social networking through the lived common experiences of 7 college students. The problem of the study was a lack of learner voice in understanding the value of social…

  3. Going Social: The Impact of Social Networking in Promoting Education

    Science.gov (United States)

    Jain, Neelesh Kumar; Verma, Ashish; Verma, Rama Shankar; Tiwari, Prashant

    2012-01-01

    The growth and the popularity of the Social networks has a high impact on the development of the students in the field of Personality, Attitudes, Knowledge and on its whole academic performance in classroom and society. This paper envisage on the impact of Social Network on Education and Training of the students.

  4. Mining of the social network extraction

    Science.gov (United States)

    Nasution, M. K. M.; Hardi, M.; Syah, R.

    2017-01-01

    The use of Web as social media is steadily gaining ground in the study of social actor behaviour. However, information in Web can be interpreted in accordance with the ability of the method such as superficial methods for extracting social networks. Each method however has features and drawbacks: it cannot reveal the behaviour of social actors, but it has the hidden information about them. Therefore, this paper aims to reveal such information in the social networks mining. Social behaviour could be expressed through a set of words extracted from the list of snippets.

  5. Social Networking Sites and Language Learning

    Science.gov (United States)

    Brick, Billy

    2011-01-01

    This article examines a study of seven learners who logged their experiences on the language leaning social networking site Livemocha over a period of three months. The features of the site are described and the likelihood of their future success is considered. The learners were introduced to the Social Networking Site (SNS) and asked to learn a…

  6. Social Networking on the Semantic Web

    Science.gov (United States)

    Finin, Tim; Ding, Li; Zhou, Lina; Joshi, Anupam

    2005-01-01

    Purpose: Aims to investigate the way that the semantic web is being used to represent and process social network information. Design/methodology/approach: The Swoogle semantic web search engine was used to construct several large data sets of Resource Description Framework (RDF) documents with social network information that were encoded using the…

  7. Social Networking and Academic Performance: A Review

    Science.gov (United States)

    Doleck, Tenzin; Lajoie, Susanne

    2018-01-01

    The ubiquitous use of social networking sites by students and the potential impacts of such use on academic performance are of both theoretical and practical importance. Hence, this paper addresses the question: how does the use of social networking sites influence academic performance? The present review synthesizes the empirical findings of the…

  8. The Social Dynamics of Innovation Networks

    NARCIS (Netherlands)

    Rutten, Roel; Benneworth, Paul Stephen; Irawati, Dessy; Boekema, Frans

    2014-01-01

    The social dynamics of innovation networks captures the important role of trust, social capital, institutions and norms and values in the creation of knowledge in innovation networks. In doing so, this book connects to a long-standing debate on the socio-spatial context of innovation in economic

  9. Social Networks and Corporate Information Security

    Directory of Open Access Journals (Sweden)

    Ekaterina Gennadievna Kondratova

    2013-06-01

    Full Text Available It is defined in the article social networks as a tool in the hands of cyber-criminals to compromise the organization’s data. The author focuses on a list of threats to information security caused by social networks usage, which should be considered in the set up of information security management system of the company.

  10. Social Networks: Gated Communities or Free Cantons?

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Online social networks and other cloud-based services have concentrated the control of the web in the hands of a few corporations. Our personal data has been commodified, often without our knowledge or consent. Is there a way to retain all the benefits of social networking without giving up control of our data?

  11. Designing for Privacy in Ubiquitous Social Networking

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Figueiras, Joao

    2015-01-01

    Improving human communication during face–to–face meetings is nowadays possible by transferring online social networking benefits to the physical world. This is enabled by the ubiquitous social networking services that became available by means of wirelessly interconnected smart devices...

  12. Entrepreneurial Idea Identification through Online Social Networks

    Science.gov (United States)

    Lang, Matthew C.

    2010-01-01

    The increasing use of social network websites may signal a change in the way the next generation of entrepreneurs identify entrepreneurial ideas. An important part of the entrepreneurship literature emphasizes how vital the use of social networks is to entrepreneurial idea identification, opportunity recognition, and ultimately new venture…

  13. Social networking for well-being

    NARCIS (Netherlands)

    Steen, M.G.D.; Aarts, O.A.J.; Broekman, C.C.M.T.; Prins, S.C.L.

    2011-01-01

    In this paper, we present some of the work that is being done in the WeCare project (in the AAL programme). The project’s goal is to introduce social networking services in the lives of older people, in order to improve their well-being. Participation in social networks, both online and ‘in real

  14. Social network sites: Indispensable or optional social tools?

    DEFF Research Database (Denmark)

    Shklovski, Irina

    2012-01-01

    Much research has enumerated potential benefits of online social network sites. Given the pervasiveness of these sites and the numbers of people that use them daily, both re-search and media tend to make the assumption that social network sites have become indispensible to their users. Based...... on the analysis of qualitative data from users of social network sites in Russia and Kazakhstan, this paper consid-ers under what conditions social network sites can become indispensable to their users and when these technologies remain on the periphery of life despite fulfilling useful func-tions. For some...... respondents, these sites had become indis-pensable tools as they were integrated into everyday rou-tines of communicating with emotionally important and proximal contacts and were often used for coordination of offline activities. For others social network sites remained spaces where they occasionally visited...

  15. Towards a Formal Model of Social Data

    DEFF Research Database (Denmark)

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

    , transform, analyse, and report social data from social media platforms such as Facebook and twitter. Formal methods, models and tools for social data are largely limited to graph theoretical approaches informing conceptual developments in relational sociology and methodological developments in social...... network analysis. As far as we know, there are no integrated modeling approaches to social data across the conceptual, formal and software realms. Social media analytics can be undertaken in two main ways - ”Social Graph Analytics” and ”Social Text Analytics” (Vatrapu, in press/2013). Social graph......, we exemplify the semantics of the formal model with real-world social data examples. Third, we briefly present and discuss the Social Data Analytics Tool (SODATO) that realizes the conceptual model in software and provisions social data for computational social science analysis based on the formal...

  16. Applications of social media and social network analysis

    CERN Document Server

    Kazienko, Przemyslaw

    2015-01-01

    This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to commun

  17. Mining social networks and security informatics

    CERN Document Server

    Özyer, Tansel; Rokne, Jon; Khoury, Suheil

    2013-01-01

    Crime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for soci

  18. COMMUNICATION MANAGEMENT CRISIS IN SOCIAL NETWORKS

    OpenAIRE

    Ana Mª Enrique Jiménez

    2013-01-01

    It is often in the social networks where you detect the first signs of a potential crisis situation. Today, many companies decide to be present in social networks to communicate, listen and respond to their audiences openly with immediacy. A simple complaint is visible and propagates through the network in seconds, being capable of generating a negative impact on the corporate image of the organization. The same can happen to the contrary, ie, to praise the performance of a company, which may...

  19. Corporate Social Networking: Risks and Opportunities

    OpenAIRE

    Straumsheim, Jan Henrik Schou

    2011-01-01

    Social networks have seen an explosive growth over the last few years, with the most popular online services totaling over half a billion users. These networks have started permeating several aspects of our daily lives: for example by changing the ways we communicate with our friends and family, share media and organize events. Popular social networking websites like Facebook and Twitter now account for over half of the content shared on the web. Norwegian businesses are taking note, and are ...

  20. Target-Centric Network Modeling

    DEFF Research Database (Denmark)

    Mitchell, Dr. William L.; Clark, Dr. Robert M.

    In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...

  1. Analyzing negative ties in social networks

    Directory of Open Access Journals (Sweden)

    Mankirat Kaur

    2016-03-01

    Full Text Available Online social networks are a source of sharing information and maintaining personal contacts with other people through social interactions and thus forming virtual communities online. Social networks are crowded with positive and negative relations. Positive relations are formed by support, endorsement and friendship and thus, create a network of well-connected users whereas negative relations are a result of opposition, distrust and avoidance creating disconnected networks. Due to increase in illegal activities such as masquerading, conspiring and creating fake profiles on online social networks, exploring and analyzing these negative activities becomes the need of hour. Usually negative ties are treated in same way as positive ties in many theories such as balance theory and blockmodeling analysis. But the standard concepts of social network analysis do not yield same results in respect of each tie. This paper presents a survey on analyzing negative ties in social networks through various types of network analysis techniques that are used for examining ties such as status, centrality and power measures. Due to the difference in characteristics of flow in positive and negative tie networks some of these measures are not applicable on negative ties. This paper also discusses new methods that have been developed specifically for analyzing negative ties such as negative degree, and h∗ measure along with the measures based on mixture of positive and negative ties. The different types of social network analysis approaches have been reviewed and compared to determine the best approach that can appropriately identify the negative ties in online networks. It has been analyzed that only few measures such as Degree and PN centrality are applicable for identifying outsiders in network. For applicability in online networks, the performance of PN measure needs to be verified and further, new measures should be developed based upon negative clique concept.

  2. Information filtering on coupled social networks.

    Science.gov (United States)

    Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui

    2014-01-01

    In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks.

  3. Social networks, social support mechanisms, and quality of life after breast cancer diagnosis.

    Science.gov (United States)

    Kroenke, Candyce H; Kwan, Marilyn L; Neugut, Alfred I; Ergas, Isaac J; Wright, Jaime D; Caan, Bette J; Hershman, Dawn; Kushi, Lawrence H

    2013-06-01

    We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006 to 2011 and provided data on social networks (the presence of a spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible support, emotional/informational support, affection, positive social interaction), and QOL, measured by the FACT-B, approximately 2 months post diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower versus higher than median QOL scores. We further stratified by stage at diagnosis and treatment. In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR = 2.18, 95 % CI: 1.72-2.77), physical well-being (WB) (OR = 1.61, 95 % CI: 1.27-2.03), functional WB (OR = 2.08, 95 % CI: 1.65-2.63), social WB (OR = 3.46, 95 % CI: 2.73-4.39), and emotional WB (OR = 1.67, 95 % CI: 1.33-2.11) scores and higher breast cancer symptoms (OR = 1.48, 95 % CI: 1.18-1.87) compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was "positive social interaction." However, each type of support was important depending on outcome, stage, and treatment status. Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status.

  4. Social networks, social support mechanisms, and quality of life after breast cancer diagnosis

    Science.gov (United States)

    Kroenke, Candyce H; Kwan, Marilyn L.; Neugut, Alfred I.; Ergas, Isaac J.; Wright, Jaime D.; Caan, Bette J.; Hershman, Dawn; Kushi, Lawrence H.

    2013-01-01

    Purpose We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. Methods This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006-2011 and provided data on social networks (presence of spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible, emotional/informational, affection, positive social interaction), and quality of life (QOL), measured by the FACT-B, approximately two months post-diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower vs. higher than median QOL scores. We further stratified by stage at diagnosis and treatment. Results In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR=2.18, 95%CI:1.72-2.77), physical well-being (WB) (OR=1.61, 95%CI:1.27-2.03), functional WB (OR=2.08, 95%CI:1.65-2.63), social WB (OR=3.46, 95%CI:2.73-4.39), and emotional WB (OR=1.67, 95%CI:1.33-2.11) scores and higher breast cancer symptoms (OR=1.48, 95%CI:1.18-1.87), compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was “positive social interaction”. However, each type of support was important depending on outcome, stage, and treatment status. Conclusions Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status. PMID:23657404

  5. Consumer engagement in social networks brand community

    OpenAIRE

    Rybakovas, Paulius

    2016-01-01

    Consumers increasingly integrate social media into their day-to-day lives. For companies consumer engagement in a brand community on social network is becoming increasingly important for developing relations with consumers. Consumer engagement in a brand community on social network creates a dynamic relationship between the community members and the brand which contributes to an increase in consumer loyalty to the brand. The literature is abundant of studies, which examines the consumer engag...

  6. Social Networks: Rational Learning and Information Aggregation

    Science.gov (United States)

    2009-09-01

    predecessor, Gale and Kariv (2003) who generalize the payoff equalization result of Bala and Goyal (1998) in connected social networks (discussed below...requires more notation. Using Bayes’ Rule and the assumption of equal priors on the state θ, we have that the social belief given by observing... Social Networks: Rational Learning and Information Aggregation by Ilan Lobel B.Sc., Pontif́ıcia Universidade Católica do Rio de Janeiro (2004

  7. Friend suggestion in social network based on user log

    Science.gov (United States)

    Kaviya, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.

    2017-11-01

    Simple friend recommendation algorithms such as similarity, popularity and social aspects is the basic requirement to be explored to methodically form high-performance social friend recommendation. Suggestion of friends is followed. No tags of character were followed. In the proposed system, we use an algorithm for network correlation-based social friend recommendation (NC-based SFR).It includes user activities like where one lives and works. A new friend recommendation method, based on network correlation, by considering the effect of different social roles. To model the correlation between different networks, we develop a method that aligns these networks through important feature selection. We consider by preserving the network structure for a more better recommendations so that it significantly improves the accuracy for better friend-recommendation.

  8. Factors Enabling Information Propagation in a Social Network Site

    DEFF Research Database (Denmark)

    Magnani, Matteo; Montesi, Danilo; Rossi, Luca

    2013-01-01

    A relevant feature of Social Network Sites is their ability to propagate units of information and create large distributed conversations. This phenomenon is particularly relevant because of the speed of information propagation, which is known to be much faster than within traditional media......, and because of the very large amount of people that can potentially be exposed to information items. While many general formal models of network propagation have been developed in different research fields, in this chapter we present the result of an empirical study on a Large Social Database (LSD) aimed...... at measuring specific socio-technical factors enabling information spreading in Social Network Sites....

  9. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira

    2016-01-01

    The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

  10. Social Network Sites, Individual Social Capital and Happiness

    NARCIS (Netherlands)

    E. Arampatzi (Efstratia); M.J. Burger (Martijn); N.A. Novik (Natallia)

    2016-01-01

    textabstractCan online social contacts replace the importance of real-life social connections in our pursuit of happiness? With the growing use of social network sites (SNSs), attention has been increasingly drawn to this topic. Our study empirically examines the effect of SNS use on happiness for

  11. One Health in social networks and social media.

    Science.gov (United States)

    Mekaru, S R; Brownstein, J S

    2014-08-01

    In the rapidly evolving world of social media, social networks, mobile applications and citizen science, online communities can develop organically and separately from larger or more established organisations. The One Health online community is experiencing expansion from both the bottom up and the top down. In this paper, the authors review social media's strengths and weaknesses, earlier work examining Internet resources for One Health, the current state of One Health in social media (e.g. Facebook, Twitter, YouTube) and online social networking sites (e.g. LinkedIn and ResearchGate), as well as social media in One Health-related citizen science projects. While One Health has a fairly strong presence on websites, its social media presence is more limited and has an uneven geographic distribution. In work following the Stone Mountain Meeting,the One Health Global Network Task Force Report recommended the creation of an online community of practice. Professional social networks as well as the strategic use of social media should be employed in this effort. Finally, One Health-related research projects using volunteers (citizen science) often use social media to enhance their recruitment. Including these researchers in a community of practitioners would take full advantage of their existing social media presence. In conclusion, the interactive nature of social media, combined with increasing global Internet access, provides the One Health community with opportunities to meaningfully expand their community and promote their message.

  12. Threshold Learning Dynamics in Social Networks

    Science.gov (United States)

    González-Avella, Juan Carlos; Eguíluz, Victor M.; Marsili, Matteo; Vega-Redondo, Fernado; San Miguel, Maxi

    2011-01-01

    Social learning is defined as the ability of a population to aggregate information, a process which must crucially depend on the mechanisms of social interaction. Consumers choosing which product to buy, or voters deciding which option to take with respect to an important issue, typically confront external signals to the information gathered from their contacts. Economic models typically predict that correct social learning occurs in large populations unless some individuals display unbounded influence. We challenge this conclusion by showing that an intuitive threshold process of individual adjustment does not always lead to such social learning. We find, specifically, that three generic regimes exist separated by sharp discontinuous transitions. And only in one of them, where the threshold is within a suitable intermediate range, the population learns the correct information. In the other two, where the threshold is either too high or too low, the system either freezes or enters into persistent flux, respectively. These regimes are generally observed in different social networks (both complex or regular), but limited interaction is found to promote correct learning by enlarging the parameter region where it occurs. PMID:21637714

  13. Spreading paths in partially observed social networks

    OpenAIRE

    Onnela, Jukka-Pekka; Christakis, Nicholas A.

    2012-01-01

    Understanding how and how far information, behaviors, or pathogens spread in social networks is an important problem, having implications for both predicting the size of epidemics, as well as for planning effective interventions. There are, however, two main challenges for inferring spreading paths in real-world networks. One is the practical difficulty of observing a dynamic process on a network, and the other is the typical constraint of only partially observing a network. Using a static, s...

  14. Web Mining and Social Networking

    DEFF Research Database (Denmark)

    Xu, Guandong; Zhang, Yanchun; Li, Lin

    This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web ...... sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.......This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web...... mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal...

  15. Organ trade using social networks.

    Science.gov (United States)

    Alrogy, Waleed; Jawdat, Dunia; Alsemari, Muhannad; Alharbi, Abdulrahman; Alasaad, Abdullah; Hajeer, Ali H

    2016-01-01

    Organ transplantation is recognized worldwide as an effective treatment for organ failure. However, due to the increase in the number of patients requiring a transplant, a shortage of suitable organs for transplantation has become a global problem. Human organ trade is an illegal practice of buying or selling organs and is universally sentenced. The aim of this study was to search social network for organ trade and offerings in Saudi Arabia. The study was conducted from June 22, 2015 to February 19, 2016. The search was conducted on Twitter, Google answers, and Facebook using the following terms: kidney for sale, kidneys for sale, liver for sale, kidney wanted, liver wanted, kidney donor, and liver donor. We found a total of 557 adverts on organ trade, 165 (30%) from donors or sellers, and 392 (70%) from recipients or buyers. On Twitter, we found 472 (85%) adverts, on Google answers 61 (11%), and on Facebook 24 (4%). Organ trade is a global problem, and yet it is increasingly seen in many countries. Although the Saudi Center for Organ Transplantation by-laws specifically prohibits and monitors any form of commercial transplantation, it is still essential to enforce guidelines for medical professionals to detect and prevent such criminal acts.

  16. Organ trade using social networks

    Directory of Open Access Journals (Sweden)

    Waleed Alrogy

    2016-01-01

    Full Text Available Organ transplantation is recognized worldwide as an effective treatment for organ failure. However, due to the increase in the number of patients requiring a transplant, a shortage of suitable organs for transplantation has become a global problem. Human organ trade is an illegal practice of buying or selling organs and is universally sentenced. The aim of this study was to search social network for organ trade and offerings in Saudi Arabia. The study was conducted from June 22, 2015 to February 19, 2016. The search was conducted on Twitter, Google answers, and Facebook using the following terms: kidney for sale, kidneys for sale, liver for sale, kidney wanted, liver wanted, kidney donor, and liver donor. We found a total of 557 adverts on organ trade, 165 (30% from donors or sellers, and 392 (70% from recipients or buyers. On Twitter, we found 472 (85% adverts, on Google answers 61 (11%, and on Facebook 24 (4%. Organ trade is a global problem, and yet it is increasingly seen in many countries. Although the Saudi Center for Organ Transplantation by-laws specifically prohibits and monitors any form of commercial transplantation, it is still essential to enforce guidelines for medical professionals to detect and prevent such criminal acts.

  17. Brand communities embedded in social networks ?

    OpenAIRE

    Zaglia, Melanie E.

    2013-01-01

    Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social ...

  18. Modern Social Support Structures: Online Social Networks and their Implications for Social Workers

    Directory of Open Access Journals (Sweden)

    Kala Chakradhar

    2009-03-01

    Full Text Available Mapping and assessing social networks and the quality of their social support is a valuable intervention strategy for social workers. These networks have now spread onto the digital realm in the form of Online Social Networks (OSNs. This study investigated the nature of social support provided by such networks to their users in a rural mid-South University (USA and explored parallels with the current understanding of social support in conventional social networks. A web-based survey administered to college students revealed that users of these online networks were predominantly undergraduate first year students, female, single, unemployed and from a variety of academic disciplines. The examination of the components of OSNs appears to mirror those of offline networks. They also seem to complement the effects of each other while contributing to an individual's support system. The paper concludes with critical implications of such online social networking for University students and social workers in practice and education.

  19. [Social networks in drinking behaviors among Japanese: support network, drinking network, and intervening network].

    Science.gov (United States)

    Yoshihara, Chika; Shimizu, Shinji

    2005-10-01

    The national representative sample was analyzed to examine the relationship between respondents' drinking practice and the social network which was constructed of three different types of network: support network, drinking network, and intervening network. Non-parametric statistical analysis was conducted with chi square method and ANOVA analysis, due to the risk of small samples in some basic tabulation cells. The main results are as follows: (1) In the support network of workplace associates, moderate drinkers enjoyed much more sociable support care than both nondrinkers and hard drinkers, which might suggest a similar effect as the French paradox. Meanwhile in the familial and kinship network, the more intervening care support was provided, the harder respondents' drinking practice. (2) The drinking network among Japanese people for both sexes is likely to be convergent upon certain types of network categories and not decentralized in various categories. This might reflect of the drinking culture of Japan, which permits people to drink everyday as a practice, especially male drinkers. Subsequently, solitary drinking is not optional for female drinkers. (3) Intervening network analysis showed that the harder the respondents' drinking practices, the more frequently their drinking behaviors were checked in almost all the categories of network. A rather complicated gender double-standard was found in the network of hard drinkers with their friends, particularly for female drinkers. Medical professionals played a similar intervening role for men as family and kinship networks but to a less degree than friends for females. The social network is considerably associated with respondents' drinking, providing both sociability for moderate drinkers and intervention for hard drinkers, depending on network categories. To minimize the risk of hard drinking and advance self-healthy drinking there should be more research development on drinking practice and the social network.

  20. SOCIAL NETWORKS AS DISPOSITIVES OF NEOLIBERAL GOVERNMENTALITY

    Directory of Open Access Journals (Sweden)

    Julio Cesar Lemes de Castro

    2016-10-01

    Full Text Available This article of theoretical reflection investigates the social networks that emerge in the context of Web 2.0, such as Facebook, as dispositives of neoliberal governmentality in the sense proposed by Foucault. From the standpoint of government of self, the design of social networks establishes a competition for attention that tends to favor the neoliberal culture of performance. In terms of social organization, the way in which users intertwine their connections is paralleled by the neoliberal paradigm of spontaneous market order. Furthermore, the use of personal information on these users, encompassing all their activities within the networks, in order to set up databases to attract advertisers reflects the neoliberal tendency of colonization of the different realms of existence by economic forces. However, the tensions that accompany neoliberal governmentality in social networks reveal its limitations, opening the possibility for these networks to also act as instruments of resistance to neoliberalism.

  1. Contributions of Social Networking for Innovation

    Directory of Open Access Journals (Sweden)

    Daniela Maria Cartoni

    2013-04-01

    Full Text Available This paper investigates the role of virtual social networks as a mechanism complementary to formal channels of technology transfer represented by ICT and by private centers of R & D in industry. The strengthening of Web 2.0 has provided the expansion of collaborative tools, in particular the social networks, with a strong influence on the spread of knowledge and innovation. To evaluate the potential of virtual networks, a survey had been conducted to identify and describe the characteristics of some of the major social networks used in Brazil (LinkedIn, Orkut and Twitter. Even this phenomenon is not mature, the study identified the potential and benefits of social networks as informal structures that help in generation of knowledge and innovation diffusion, as a field to be explored and developed.

  2. The co-evolution of cultures, social network communities, and agent locations in an extension of Axelrod’s model of cultural dissemination

    Science.gov (United States)

    Pfau, Jens; Kirley, Michael; Kashima, Yoshihisa

    2013-01-01

    We introduce a variant of the Axelrod model of cultural dissemination in which agents change their physical locations, social links, and cultures. Numerical simulations are used to investigate the evolution of social network communities and the cultural diversity within and between these communities. An analysis of the simulation results shows that an initial peak in the cultural diversity within network communities is evident before agents segregate into a final configuration of culturally homogeneous communities. Larger long-range interaction probabilities facilitate the initial emergence of culturally diverse network communities, which leads to a more pronounced initial peak in cultural diversity within communities. At equilibrium, the number of communities, and hence cultures, increases when the initial cultural diversity increases. However, the number of communities decreases when the lattice size or population density increases. A phase transition between two regimes of initial cultural diversity is evident. For initial diversities below a critical value, a single network community and culture emerges that dominates the population. For initial diversities above the critical value, multiple culturally homogeneous communities emerge. The critical value of initial diversity at which this transition occurs increases with increasing lattice size and population density and generally with increasing absolute population size. We conclude that larger initial diversities promote cultural heterogenization, while larger lattice sizes, population densities, and in fact absolute population sizes promote homogenization.

  3. El videojuego en red social: un nuevo modelo de comunicación / Videojuego in social network: a new model of communication

    Directory of Open Access Journals (Sweden)

    Francisco Ignacio Revuelta Domínguez

    2012-07-01

    Full Text Available Resumen: Los videojuegos en las redes sociales son la combinación de una evolución paralela, por un lado el desarrollo del entretenimiento y las interfaces interactivas y, por otro, la evolución de los nuevos medios de comunicación, con Internet a la cabeza. Pasando por el correo electrónico y desarrollándose en múltiples direcciones, parece que las redes sociales se han convertido en el actual estándar de comunicación social, no solo en entornos grupales, sino de transmisión de información masiva de un modo viral. Una estructura no jerarquizada que ha conseguido atraer a más de 600 millones de usuarios y, con ellos, un enorme negocio. Como otros tantos, el videojuego se adentra en estos sites, un entorno que le es natural en un principio, recogiendo los frutos de los juegos multijugador masivos, pero pronto se enriquece adaptándose al medio y creando nuestras estructuras comunicacionales adecuadas a una nueva y desconocida situación. Como en otras aplicaciones de las TIC en ámbitos educativos, el videojuego puede ser utilizado con estos fines; no sólo con proyectos infantiles ni programas interactivos dedicados a la enseñanza, sino como videojuegos intrínsecamente. Casos como los serious games nos muestran las enormes posibilidades que tienen a distintos niveles. Para el caso de los videojuegos sociales, las opciones pedagógicas multiplican sus posibilidades al acceder a un público masivo con estructuras que, si bien pueden alejarse de los clásicos procedimientos educativos, sí que se fundamentan sobre estas bases ya que permiten una distribución rápida, barata y de acceso sencillo, sin que representen para el usuario una carga, sino un aprendizaje pasivo. Por ello, es importante preguntarse cómo se desarrolla un videojuego social, cuál es su narrativa, cómo se comportan los individuos ante él y, sobre todo, cómo podemos orientarlo hacia nuestros objetivos.Abstract: Videogames in social networks are a combination of

  4. Social network analysis of study environment

    Directory of Open Access Journals (Sweden)

    Blaženka Divjak

    2010-06-01

    Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.

  5. Volunteerism: Social Network Dynamics and Education

    Science.gov (United States)

    Ajrouch, Kristine J.; Antonucci, Toni C.; Webster, Noah J.

    2016-01-01

    Objectives . We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. Methods . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. Results . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. Discussion . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. PMID:25512570

  6. COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks

    NARCIS (Netherlands)

    Sie, Rory

    2012-01-01

    Sie, R. L. L. (2012). COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks (Unpublished doctoral dissertation). September, 28, 2012, Open Universiteit in the Netherlands (CELSTEC), Heerlen, The Netherlands.

  7. Urbanism, Neighborhood Context, and Social Networks.

    Science.gov (United States)

    Cornwell, Erin York; Behler, Rachel L

    2015-09-01

    Theories of urbanism suggest that the urban context erodes individuals' strong social ties with friends and family. Recent research has narrowed focus to the neighborhood context, emphasizing how localized structural disadvantage affects community-level cohesion and social capital. In this paper, we argue that neighborhood context also shapes social ties with friends and family- particularly for community-dwelling seniors. We hypothesize that neighborhood disadvantage, residential instability, and disorder restrict residents' abilities to cultivate close relationships with neighbors and non-neighbor friends and family. Using data from the National Social Life, Health, and Aging Project (NSHAP), we find that older adults who live in disadvantaged neighborhoods have smaller social networks. Neighborhood disadvantage is also associated with less close network ties and less frequent interaction - but only among men. Furthermore, residents of disordered neighborhoods have smaller networks and weaker ties. We urge scholars to pay greater attention to how neighborhood context contributes to disparities in network-based access to resources.

  8. Benford's Law Applies to Online Social Networks.

    Science.gov (United States)

    Golbeck, Jennifer

    2015-01-01

    Benford's Law states that, in naturally occurring systems, the frequency of numbers' first digits is not evenly distributed. Numbers beginning with a 1 occur roughly 30% of the time, and are six times more common than numbers beginning with a 9. We show that Benford's Law applies to social and behavioral features of users in online social networks. Using social data from five major social networks (Facebook, Twitter, Google Plus, Pinterest, and LiveJournal), we show that the distribution of first significant digits of friend and follower counts for users in these systems follow Benford's Law. The same is true for the number of posts users make. We extend this to egocentric networks, showing that friend counts among the people in an individual's social network also follows the expected distribution. We discuss how this can be used to detect suspicious or fraudulent activity online and to validate datasets.

  9. Benford's Law Applies to Online Social Networks.

    Directory of Open Access Journals (Sweden)

    Jennifer Golbeck

    Full Text Available Benford's Law states that, in naturally occurring systems, the frequency of numbers' first digits is not evenly distributed. Numbers beginning with a 1 occur roughly 30% of the time, and are six times more common than numbers beginning with a 9. We show that Benford's Law applies to social and behavioral features of users in online social networks. Using social data from five major social networks (Facebook, Twitter, Google Plus, Pinterest, and LiveJournal, we show that the distribution of first significant digits of friend and follower counts for users in these systems follow Benford's Law. The same is true for the number of posts users make. We extend this to egocentric networks, showing that friend counts among the people in an individual's social network also follows the expected distribution. We discuss how this can be used to detect suspicious or fraudulent activity online and to validate datasets.

  10. How can social network analysis contribute to social behavior research in applied ethology?

    Science.gov (United States)

    Makagon, Maja M; McCowan, Brenda; Mench, Joy A

    2012-05-01

    Social network analysis is increasingly used by behavioral ecologists and primatologists to describe the patterns and quality of interactions among individuals. We provide an overview of this methodology, with examples illustrating how it can be used to study social behavior in applied contexts. Like most kinds of social interaction analyses, social network analysis provides information about direct relationships (e.g. dominant-subordinate relationships). However, it also generates a more global model of social organization that determines how individual patterns of social interaction relate to individual and group characteristics. A particular strength of this approach is that it provides standardized mathematical methods for calculating metrics of sociality across levels of social organization, from the population and group levels to the individual level. At the group level these metrics can be used to track changes in social network structures over time, evaluate the effect of the environment on social network structure, or compare social structures across groups, populations or species. At the individual level, the metrics allow quantification of the heterogeneity of social experience within groups and identification of individuals who may play especially important roles in maintaining social stability or information flow throughout the network.

  11. Bidirectional selection between two classes in complex social networks.

    Science.gov (United States)

    Zhou, Bin; He, Zhe; Jiang, Luo-Luo; Wang, Nian-Xin; Wang, Bing-Hong

    2014-12-19

    The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We demonstrated theoretically that the rate of successfully matching is affected greatly by individuals' neighborhoods in social networks, regardless of the type of networks. Furthermore, it is found that the high average degree of networks contributes to increasing rates of successful matches. The matching performance in different types of networks has been quantitatively investigated, revealing that the small-world networks reinforces the matching rate more than scale-free networks at given average degree. In addition, our analysis is consistent with the modeling result, which provides the theoretical understanding of underlying mechanisms of matching in complex networks.

  12. Predicting Positive and Negative Relationships in Large Social Networks.

    Directory of Open Access Journals (Sweden)

    Guan-Nan Wang

    Full Text Available In a social network, users hold and express positive and negative attitudes (e.g. support/opposition towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM. Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

  13. Emergence of communities and diversity in social networks.

    Science.gov (United States)

    Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross; Stanley, H Eugene

    2017-03-14

    Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics.

  14. Factors which motivate the use of social networks by students.

    Science.gov (United States)

    González Sanmamed, Mercedes; Muñoz Carril, Pablo C; Dans Álvarez de Sotomayor, Isabel

    2017-05-01

    The aim of this research was to identify those factors which motivate the use of social networks by 4th year students in Secondary Education between the ages of 15 and 18. 1,144 students from 29 public and private schools took part. The data were analysed using Partial Least Squares Structural Equation Modelling technique. Versatility was confirmed to be the variable which most influences the motivation of students in their use of social networks. The positive relationship between versatility in the use of social networks and educational uses was also significant. The characteristics of social networks are analysed according to their versatility and how this aspect makes them attractive to students. The positive effects of social networks are discussed in terms of educational uses and their contribution to school learning. There is also a warning about the risks associated with misuse of social networks, and finally, the characteristics and conditions for the development of good educational practice through social networks are identified.

  15. Using Social Network Analysis to Investigate Positive EOL Communication.

    Science.gov (United States)

    Xu, Jiayun; Yang, Rumei; Wilson, Andrew; Reblin, Maija; Clayton, Margaret F; Ellington, Lee

    2018-04-30

    End of life (EOL) communication is a complex process involving the whole family and multiple care providers. Applications of analysis techniques that account for communication beyond the patient and patient/provider, will improve clinical understanding of EOL communication. To introduce the use of social network analysis to EOL communication data, and to provide an example of applying social network analysis to home hospice interactions. We provide a description of social network analysis using social network analysis to model communication patterns during home hospice nursing visits. We describe three social network attributes (i.e. magnitude, directionality, and reciprocity) in the expression of positive emotion among hospice nurses, family caregivers, and hospice cancer patients. Differences in communication structure by primary family caregiver gender and across time were also examined. Magnitude (frequency) in the expression of positive emotion occurred most often between nurses and caregivers or nurses and patients. Female caregivers directed more positive emotion to nurses, and nurses directed more positive emotion to other family caregivers when the primary family caregiver was male. Reciprocity (mutuality) in positive emotion declined towards day of death, but increased on day of actual patient death. There was variation in reciprocity by the type of positive emotion expressed. Our example demonstrates that social network analysis can be used to better understand the process of EOL communication. Social network analysis can be expanded to other areas of EOL research, such as EOL decision-making and health care teamwork. Copyright © 2018. Published by Elsevier Inc.

  16. Predicting Positive and Negative Relationships in Large Social Networks.

    Science.gov (United States)

    Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N A; Fu, Yan

    2015-01-01

    In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods.

  17. The Freddi Staurs of Social Networking - A Legal Approach

    OpenAIRE

    Kosta , Eleni

    2009-01-01

    International audience; One of the most remarkable cultural phenomena that blossomed in the Web 2.0 era are the social networking sites, such as Facebook, MySpace, Friendster, Bebo, Netlog or LinkedIn. The introduction of new communication channels facilitates interactive information sharing and collaboration between various actors over social networking sites. These actors, i.e. the providers and the users, do not always fit in the traditional communications models. In this paper we are goin...

  18. Regional Use of Social Networking Tools

    Science.gov (United States)

    2014-12-01

    4 2.1.7 Tumblr 4 2.1.8 Instagram 4 2.2 Local Social Networking Services 5 3 Regional Preferences for Social Networking Tools 6 4 African Region...YouTube 280 million Twitter 255 million LinkedIn n/a Pinterest n/a Tumblr 300 million Instagram 200 million The active-user base numbers...so this percentage may decline in the future. 2.1.8 Instagram Instagram , acquired by Facebook in 2012, is a mobile social networking service that

  19. The genre tutorial and social networks terminology

    Directory of Open Access Journals (Sweden)

    Márcio Sales Santiago

    2014-02-01

    Full Text Available This paper analyzes the terminology in the Internet social networks tutorials. A tutorial is a specialized text, full of terms, aiming to teach an individual or group of individuals who need some guidelines to operationalize a computerized tool, such as a social network. It is necessary to identify linguistic and terminological characteristics from the specialized lexical units in this digital genre. Social networks terminology is described and exemplified here. The results show that it is possible to refer to two specific terminologies in tutorials which help to determine the terminological profile of the thematic area, specifically from the point of view of denomination.

  20. An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks.

    Directory of Open Access Journals (Sweden)

    Emily Silver Huff

    Full Text Available Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner's management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of 'harvest readiness' and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking. Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior.