Emergence of complex social networks from spatial structure and rules of thumb: a modelling approach

Individual-based computer models show that simple heuristic governing individuals’ behavior may suffice to generate complex patterns of social behavior at the group level such as those observed in animal societies. ‘GrooFiWorld’ is an example of such kind of computer models. In this model, self-organization and simple behavioral rules generate complex patterns of social behavior like those described in tolerant and intolerant societies of macaques. Social complexity results from the socio-spatial structure of the group, the nature of which is, in turn, a side-effect of intensity of aggression. The model suggests that a similar mechanism may give rise to complex social structures in macaques. It is, however, unknown if the spatial structure of the model and that of macaques are indeed similar. Here we used social networks analysis as a proxy for spatial structure of the group. Our findings show that the social networks of the model share similar qualitative features with those of macaques. As group size increases, the density and the average individual eigenvector centrality decrease and the modularity and centralization of the network increase. In social networks emerging from simulations resembling intolerant societies the density is lower, the modularity and centralization are higher, and the individuals ranking higher in the dominance hierarchy are more central than in the social networks emerging from simulations resembling egalitarian societies. Given the qualitative similarity between the social networks of the model and that of empirical data, our results suggest that the spatial structure of macaques is similar to that of the model. It seems thus plausible that, as in the model, the spatial structure combined with simple behavioral rules plays a role in the emergence of complex social networks and complex social behavior in macaques.