IEEE Transactions on Computational Social Systems

Issue 1 • March 2014

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  • Table of contents

    Publication Year: 2014, Page(s): C1
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  • IEEE publication information

    Publication Year: 2014, Page(s): C2
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  • Inaugural Issue Editorial

    Publication Year: 2014, Page(s):1 - 2
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  • A Tutorial on Interactive Sensing in Social Networks

    Publication Year: 2014, Page(s):3 - 21
    Cited by:  Papers (17)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1657 KB) | HTML iconHTML

    This paper considers models and algorithms for interactive sensing in social networks in which individuals act as sensors and the information exchange between individuals is exploited to optimize sensing. Social learning is used to model the interaction between individuals that aim to estimate an underlying state of nature. In this context, the following questions are addressed: how can self-inter... View full abstract»

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  • Sensing, Understanding, and Shaping Social Behavior

    Publication Year: 2014, Page(s):22 - 34
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1047 KB) | HTML iconHTML

    The ability to understand social systems through the aid of computational tools is central to the emerging field of computational social systems. Such understanding can answer epistemological questions on human behavior in a data-driven manner, and provide prescriptive guidelines for persuading humans to undertake certain actions in real-world social scenarios. The growing number of works in this ... View full abstract»

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  • An Analytical Comparison of Social Network Measures

    Publication Year: 2014, Page(s):35 - 45
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1925 KB) | HTML iconHTML

    Network science spans many different fields of study, ranging from psychology to biology to the social sciences. A number of descriptive network measures have been identified for use within these fields; however, little research examines the relationships of these measures for possible statistical dependence. The research presented in this paper uses Spearman's rank correlation coefficient to exam... View full abstract»

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  • Community Detection via Maximization of Modularity and Its Variants

    Publication Year: 2014, Page(s):46 - 65
    Cited by:  Papers (22)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3652 KB) | HTML iconHTML

    In this paper, we first discuss the definition of modularity (Q) used as a metric for community quality and then we review the modularity maximization approaches which were used for community detection in the last decade. Then, we discuss two opposite yet coexisting problems of modularity optimization; in some cases, it tends to favor small communities over large ones while in others, large commun... View full abstract»

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  • A Survey of Quantitative Models of Terror Group Behavior and an Analysis of Strategic Disclosure of Behavioral Models

    Publication Year: 2014, Page(s):66 - 88
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5799 KB) | HTML iconHTML

    There are many applications (e.g., counter-terrorism) where we can automatically learn a quantitative model from realworld data about terror group behavior. In this paper, we first provide a survey of quantitative models of terrorist groups. To date, however, the best-known quantitative models of terror group behavior are based on various types of quantitative logic programs. After our survey, we ... View full abstract»

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  • Modeling Temporal Activity Patterns in Dynamic Social Networks

    Publication Year: 2014, Page(s):89 - 107
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3548 KB) | HTML iconHTML

    The focus of this work is on developing probabilistic models for temporal activity of users in social networks (e.g., posting and tweeting) by incorporating the social network influence as perceived by the user. Although prior work in this area has developed sophisticated models for user activity, these models either ignore social network influence completely or incorporate it in an implicit manne... View full abstract»

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  • Semantic Stability and Implicit Consensus in Social Tagging Streams

    Publication Year: 2014, Page(s):108 - 120
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1494 KB) | HTML iconHTML

    One potential disadvantage of social tagging systems is that due to the lack of a centralized vocabulary, a crowd of users may never manage to reach a consensus on the description of resources (e.g., books, images, users, or songs) on the Web. Yet, previous research has provided interesting evidence that the tag distributions of resources in social tagging systems may become semantically stable ov... View full abstract»

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  • IEEE Transactions on Computational Social Systems society information

    Publication Year: 2014, Page(s): C3
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  • IEEE Transactions on Computational Social Systems information for authors

    Publication Year: 2014, Page(s): C4
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Aims & Scope

IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective.

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Meet Our Editors

Editor-in-Chief
Fei-Yue Wang
University of Chinese Academy of Science
Beijing, China
Email: feiyue.trans@gmail.com