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Identification of Social Tension in Organizational Networks

Relating Clan/Clique Formation to Social Tension

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Book cover Complex Networks

Part of the book series: Studies in Computational Intelligence ((SCI,volume 207))

Abstract

Analysis of email networks reveals properties similar to classic social networks such as homophily (assortativity) and community formation. The technology underlying email enables the formation of a network but it does not explain characteristics of the network that occur only as a result of patterns in human social behavior. Accordingly, a network formed from email activity correlates to the social environment and the dynamics of the environment used to create the network. Furthermore, the overall social behavior observed in an organization may be attributed directly to the organization’s strength and resilience. When an organization is in trouble, we observe social tension among its employees. That being the case, one should be able to discern this tension by examining properties of a social network of the employees-the network should reflect the employees’mood; the fears, worries, gossips that are circulating, the good and the bad, are all reflected in organization’s social network. One of the best representations of the true social organizational social network can be constructed from email exchange. The issue we investigate in this paper relates to timing: when does the network exhibits social tension when it is known to be present in the organization? In this paper, we provide a temporal analysis of the email social network constructed for the Enron Corporation and show that changes in network characteristics strongly correlate to real-world events in that organization. More importantly, we show that this correlation is time-shifted and appears in the network before the event becomes common knowledge; our hypothesis is that we can use the anomalies in the network to identify social tension in the organization and consequently help mitigate its consequences.

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Collingsworth, B., Menezes, R. (2009). Identification of Social Tension in Organizational Networks. In: Fortunato, S., Mangioni, G., Menezes, R., Nicosia, V. (eds) Complex Networks. Studies in Computational Intelligence, vol 207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01206-8_18

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  • DOI: https://doi.org/10.1007/978-3-642-01206-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01205-1

  • Online ISBN: 978-3-642-01206-8

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