When group level is different from the population level: an adaptive network with the Deffuant model

Details When group level is different from the population level: an adaptive network with the Deffuant model When group level is different from the population level: an adaptive network with the Deffuant model

2010-02-09

arxiv.org/abs/1002.1896v2

Physics

Physics and Society

7 pages, 5 figures, Proc of 5th Int. Workshop on Emergent Intelligence on networked Agents, Toronto 2010

Scientific paper

We propose a model coupling the classical opinion dynamics of the bounded confidence model, proposed by Deffuant et al., with an adaptive network forming a community or group structure. At each step, an individual can decide if it changes groups or interact on its opinion with one of its internal or external neighbour. If it decides to look at the group level, it changes groups if its opinion is far from the average of its group from more than a threshold. If it is the case, it joins the group which has proportionally the closest average opinion from its. If it decides to interact with one of its neighbour, it becomes closer in opinion to it when its opinion and the one of the selected-to-interact neighbour are less distant from the threshold. From the study of this coupled model, we discover some surprising behaviours compared to the known behaviour of the Deffuant bounded confidence model(BC): The coupled model exhibits a total consensus for an threshold value lower than the BC model; the distribution of sizes of the groups changes: some groups become larger while other decrease in size, sometimes until containing only one individual; from the point of view of the groups, the consensus remains for a large set of threshold values while, looking at the population level, there are a lot of opinion clusters.

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