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Simple Heuristics in Complex Networks: Models of Social Influence

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Abstract

The concept of heuristic decision making is adapted to dynamic influence processes in social networks. We report results of a set of simulations, in which we systematically varied: a) the agents' strategies for contacting fellow group members and integrating collected information, and (b) features of their social environment—the distribution of members' status, and the degree of clustering in their network. As major outcome variables, we measured the speed with which the process settled, the distributions of agents' final preferences, and the rate with which high-status members changed their initial preferences. The impact of the agents' decision strategies on the dynamics and outcomes of the influence process depended on features of their social environment. This held in particular true when agents contacted all of the neighbors with whom they were connected. When agents focused on high-status members and did not contact low-status neighbors, the process typically settled more quickly, yielded larger majority factions and fewer preference changes. A case study exemplifies the empirical application of the model.

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  • Gero Schwenk & Torsten Reimer, 2008. "Simple Heuristics in Complex Networks: Models of Social Influence," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(3), pages 1-4.
    • Handle: RePEc:jas:jasssj:2007-86-2
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    1. Ron Sun & Isaac Naveh, 2004. "Simulating Organizational Decision-Making Using a Cognitively Realistic Agent Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 7(3), pages 1-5.
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