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Extensive empirical evidence suggests that there is a maximal number of people with whom an individual can maintain stable social relationships (the Dunbar number). We argue that this arises as a consequence of a natural phase transition in the dynamic self-organization among N individuals within a social system. We present the calculated size dependence of the scaling properties of complex social network models to argue that this collective behavior is an enhanced form of collective intelligence. Direct calculation establishes that the complexity of social networks as measured by their scaling behavior is nonmonotonic, peaking around 150, thereby providing a theoretical basis for the value of the Dunbar number. Thus, we establish a theory-based bridge spanning the gap between sociology and psychology.

Original publication




Journal article


Proc Natl Acad Sci U S A

Publication Date





18355 - 18358


Dunbar number, allometry relation, complexity, functionality/size, network calculations, Algorithms, Group Processes, Humans, Interpersonal Relations, Models, Theoretical, Social Behavior, Social Networking