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Uncovering the effect of dominant attributes on community topology: A case of facebook networks

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  • Yi-Shan Sung

    (The Pennsylvania State University)

  • Dashun Wang

    (Northwestern University)

  • Soundar Kumara

    (The Pennsylvania State University)

Abstract

Community structure points to structural patterns and reflects organizational or functional associations of networks. In real networks, each node usually contains multiple attributes representing the node’s characteristics. It is difficult to identify the dominant attributes, which have definitive effects on community formation. In this paper, we obtain the overlapping communities using game-theoretic clustering and focus on identifying the dominant attributes in terms of each community. We uncover the association of attributes to the community topology by defining dominance ratio and applying Pearson correlation. We test our method on Facebook data of 100 universities and colleges in the U.S. The study enables an integrating observation on how the offline lives infer online consequences. The results showed that people in class year 2010 and people studying in the same major tend to form denser and smaller groups on Facebook. Such information helps e-marketing campaigns target right customers based on demographic information and without the knowledge of underlying social networks.

Suggested Citation

  • Yi-Shan Sung & Dashun Wang & Soundar Kumara, 2018. "Uncovering the effect of dominant attributes on community topology: A case of facebook networks," Information Systems Frontiers, Springer, vol. 20(5), pages 1041-1052, October.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:5:d:10.1007_s10796-016-9696-0
    DOI: 10.1007/s10796-016-9696-0
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    References listed on IDEAS

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    Cited by:

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    2. Hao-Nan Yang & Xin-Jian Xu & Haili Liang & Xiaofan Wang, 2020. "A comparative study of online communities and popularity of BBS in four Chinese universities," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-16, June.

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