Identity-based learning and segregation in social networks under different institutional environments

Mooweon Rhee () and Tohyun Kim ()
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Mooweon Rhee: Yonsei University
Tohyun Kim: Sungkyunkwan University

Computational and Mathematical Organization Theory, 2014, vol. 20, issue 4, No 1, 339-368

Abstract: Abstract To study the evolution of segregation in social networks across systems embedded in different institutional environments, we develop an identity-based learning model where segregation is stochastically conditioned by the initial distribution of the actor’s attention to identity and the updating of this distribution over time. The updating process, which we call the process of mutual learning multiplier, is based on an actor’s success and failure experiences in tying with the same-subgroup and cross-subgroup actors. Results from a Monte Carlo simulation of the model show that the mutual learning multiplier produces disproportional relationships between the initial distribution of identity attention and the level of segregation in social networks. We also find that those relationships are affected by the actors’ attention to structural holes, rate of learning from experience, system size, and the identity heterogeneity of the system. Overall, the model provides insights into various dynamics of network structuration across time and space.

Keywords: Segregation; Social networks; Learning; Identity; Homophily (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10588-013-9169-7

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