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Inferring Social Status and Rich Club Effects in Enterprise Communication Networks

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  • Yuxiao Dong
  • Jie Tang
  • Nitesh V Chawla
  • Tiancheng Lou
  • Yang Yang
  • Bai Wang

Abstract

Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise. We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels — voice call, short message, and email — to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a “rich club” maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy.

Suggested Citation

  • Yuxiao Dong & Jie Tang & Nitesh V Chawla & Tiancheng Lou & Yang Yang & Bai Wang, 2015. "Inferring Social Status and Rich Club Effects in Enterprise Communication Networks," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-14, March.
  • Handle: RePEc:plo:pone00:0119446
    DOI: 10.1371/journal.pone.0119446
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    References listed on IDEAS

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    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Michael W Kraus & Bennett Callaghan, 2014. "Noblesse Oblige? Social Status and Economic Inequality Maintenance among Politicians," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-6, January.
    3. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
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    Cited by:

    1. Dong, Xuefan & Tang, Daisheng & Tang, Chengxiang, 2021. "Social network analysis in China’s hospital healthcare," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).

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