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Consensus and Cohesion in Simulated Social Networks

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Abstract

Social structure emerges from the interaction and information exchange between individuals in a population. The emergence of groups in animal and human social systems suggests that such social structures are the result of a cooperative and cohesive society. Using graph based models, where nodes represent individuals in a population and edges represent communication pathways, we simulate individual influence and the communication of ideas in a population. Simulations of Dunbar’s hypothesis (that natural group size in apes and humans arises from the transition from grooming behaviour to language or gossip) indicate that transmission rate and neighbourhood size accompany critical transitions of the order proposed in Dunbar’s work. We demonstrate that critical levels of connectivity are required to achieve consensus in models that simulate individual influence.

Suggested Citation

  • Rob Stocker & David Green & David Newth, 2001. "Consensus and Cohesion in Simulated Social Networks," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(4), pages 1-5.
  • Handle: RePEc:jas:jasssj:2001-5-2
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    File URL: http://jasss.soc.surrey.ac.uk/4/4/5.html
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    Cited by:

    1. Bing Wu & Shan Jiang & Hsinchun Chen, 2015. "The impact of individual attributes on knowledge diffusion in web forums," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(6), pages 2221-2236, November.

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