Data from: Better baboon breakups: collective decision theory of complex social network fissions

Many social groups are made up of complex social networks in which each individual tends to associate with a distinct subset of its groupmates. If social groups increase in size over time, competition often leads to permanent group fission. During such fissions, complex social networks present both a collective decision problem and a multidimensional optimization problem: it is advantageous for each individual to remain with their closest allies after a fission, but impossible for every individual to do so. Here, we develop computational algorithms designed to simulate group fissions in a network theoretic framework. We focus on three fission algorithms ("democracy" "community," and "despotism") that fall on a spectrum from a democratic to a dictatorial collective decision. We parameterize our social networks with data from baboons (Papio cynocephalus) and compare our simulated fissions with actual baboon fission events. We find that the democracy and community algorithms (i.e., egalitarian decisions where each individual influences the outcome) better maintain social networks during simulated fissions than despotic decisions (those driven primarily by a single individual). We also find that egalitarian decisions are good at predicting the observed individual-level outcomes of observed fissions, although the observed fissions often disturbed their social networks more than the simulated egalitarian fissions.