Consensus and cohesion in simulated social networks

Rob Stocker, David G. Green, David Newth

    Research output: Contribution to journalArticleResearchpeer-review

    36 Citations (Scopus)

    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.

    Original languageEnglish
    Number of pages16
    JournalJournal of Artificial Societies and Social Simulation
    Volume4
    Issue number4
    Publication statusPublished - Oct 2001

    Keywords

    • Artificial Societies
    • Cohesion
    • Communication
    • Complexity
    • Connectivity
    • Influence
    • Simulation
    • Social Networks

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