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  1. Convenient access to vast and untapped collections of documents generated by organizations is a highly valuable resource for research. These documents (e.g., press releases) are a window into organizational st...

    Authors: Adina Nerghes, Ju-Sung Lee, Peter Groenewegen and Iina Hellsten

    Citation: Computational Social Networks 2015 2:16

    Content type: Research

    Published on:

  2. Competitiveness is a relevant social behavior and in several contexts, from economy to sport activities, has a fundamental role. We analyze this social behavior in the domain of evolutionary game theory, using...

    Authors: Marco A Javarone and Antonio E Atzeni

    Citation: Computational Social Networks 2015 2:15

    Content type: Research

    Published on:

  3. We explore the dependence structure in the sampled sequence of complex networks. We consider randomized algorithms to sample the nodes and study extremal properties in any associated stationary sequence of cha...

    Authors: Konstantin Avrachenkov, Natalia M. Markovich and Jithin K. Sreedharan

    Citation: Computational Social Networks 2015 2:12

    Content type: Research

    Published on:

  4. This study examines the communications networks formed by direct international Internet links, weighted by bandwidth capacity, each year over the 2002–2011 period. Specifically, we analyze changes in bandwidth...

    Authors: Hyunjin Seo and Stuart Thorson

    Citation: Computational Social Networks 2015 2:11

    Content type: Research

    Published on:

  5. Social media and social networks contribute to shape the debate on societal and policy issues, but the dynamics of this process is not well understood. As a case study, we monitor Twitter activity on a wide ra...

    Authors: Borut Sluban, Jasmina Smailović, Stefano Battiston and Igor Mozetič

    Citation: Computational Social Networks 2015 2:9

    Content type: Research

    Published on:

  6. Algorithms for identifying the infection states of nodes in a network are crucial for understanding and containing epidemics and cascades. Often, however, only the infection states of a small set of nodes are ...

    Authors: Yeon-sup Lim, Bruno Ribeiro and Don Towsley

    Citation: Computational Social Networks 2015 2:8

    Content type: Research

    Published on:

  7. The critical node detection problem (CNDP) aims to fragment a graph G=(V,E) by removing a set of vertices R with cardinality |R|≤k, such that the residual graph has minimum pairwise connectivity for user-defined ...

    Authors: Mario Ventresca and Dionne Aleman

    Citation: Computational Social Networks 2015 2:6

    Content type: Research

    Published on:

  8. Dealing with big data in computational social networks may require powerful machines, big storage, and high bandwidth, which may seem beyond the capacity of small labs. We demonstrate that researchers with lim...

    Authors: Ming Jia, Hualiang Xu, Jingwen Wang, Yiqi Bai, Benyuan Liu and Jie Wang

    Citation: Computational Social Networks 2015 2:5

    Content type: Research

    Published on:

  9. Social networks are often degree correlated between nearest neighbors, an effect termed homophily, wherein individuals connect to nearest neighbors of similar connectivity. Whether friendships or other associa...

    Authors: Michael Mayo, Ahmed Abdelzaher and Preetam Ghosh

    Citation: Computational Social Networks 2015 2:4

    Content type: Research

    Published on:

  10. We study the dynamics of a game-theoretic network formation model that yields large-scale small-world networks. So far, mostly stochastic frameworks have been utilized to explain the emergence of these network...

    Authors: Omid Atabati and Babak Farzad

    Citation: Computational Social Networks 2015 2:1

    Content type: Research

    Published on:

  11. A lot of daily activities require more than one person to participate and collaborate with each other; however, for many people, it is not easy to find good partners to engage in activities with one another. W...

    Authors: Chunyu Ai, Wei Zhong, Mingyuan Yan and Feng Gu

    Citation: Computational Social Networks 2014 1:5

    Content type: Research

    Published on:

  12. The observed unbalance of spectrum utilization combined with the proliferation of wireless devices and the growth of online social networks call for a joint study of cognitive radios (CRs) and social networkin...

    Authors: Evangelos Anifantis, Eleni Stai, Vasileios Karyotis and Symeon Papavassiliou

    Citation: Computational Social Networks 2014 1:4

    Content type: Research

    Published on:

  13. This paper investigates the influence maximization (IM) problem in social networks under the linear threshold (LT) model. Kempe et al. (ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 137–146...

    Authors: Zaixin Lu, Lidan Fan, Weili Wu, Bhavani Thuraisingham and Kai Yang

    Citation: Computational Social Networks 2014 1:2

    Content type: Research

    Published on:

  14. Community partition is of great importance in sociology, biology and computer science. Due to the exponentially increasing amount of social network applications, a fast and accurate method is necessary for com...

    Authors: Zaixin Lu, Yuqing Zhu, Wei Li, Weili Wu and Xiuzhen Cheng

    Citation: Computational Social Networks 2014 1:1

    Content type: Research

    Published on:

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