Modelling a network where the opinion of each unit varies according to a majority ruling of its neighbouring units

The complexity of human behaviour can lead to very unpredictable patterns in social activity and structure. Here we demonstrate the instability of a community network controlled by majority ruling, where an element adopts the most popular opinion of their peers. We modelled a community as a square lattice, and performed sequential time step numerical calculations upon each cell in parallel. Depending on the initial ratio of two opinions, the community can segregate either into separate gangs and cliques, or get dominated by a single opinion. We also note that gangs are separated by neutral or confused groups of individuals, buffering the transition. The behaviors shown by this model can be comfortably applied to many other real life situations, such as neural or ecological networks. The results of this paper have been preliminary published in the Ref. [34].

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