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Social Relationships and the Emergence of Social Networks

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Abstract

In complex social systems such as those of many mammals, including humans, groups (and hence ego-centric social networks) are commonly structured in discrete layers. We describe a computational model for the development of social relationships based on agents' strategies for social interaction that favour more less-intense, or fewer more-intense partners. A trust-related process controls the formation and decay of relationships as a function of interaction frequency, the history of interaction, and the agents' strategies. A good fit of the observed layers of human social networks was found across a range of model parameter settings. Social interaction strategies which favour interacting with existing strong ties or a time-variant strategy produced more observation-conformant results than strategies favouring more weak relationships. Strong-tie strategies spread in populations under a range of fitness conditions favouring wellbeing, whereas weak-tie strategies spread when fitness favours foraging for food. The implications for modelling the emergence of social relationships in complex structured social networks are discussed.

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  • Alistair Sutcliffe & Di Wang & Robin Dunbar, 2012. "Social Relationships and the Emergence of Social Networks," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(4), pages 1-3.
  • Handle: RePEc:jas:jasssj:2012-34-2
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    File URL: https://www.jasss.org/15/4/3/3.pdf
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    Cited by:

    1. Fabio Lamantia & Mario Pezzino & Fabio Tramontana, 2017. "Tax Evasion, Intrinsic Motivation, and the Evolutionary Effects of Tax Reforms," Economics Discussion Paper Series 1707, Economics, The University of Manchester.

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