Modeling social cohesion with coupled oscillators: Synchrony and fragmentation

Abstract

Maintaining cohesion is a fundamental challenge in group-living species, where individuals must balance their own activity schedules with the demands of social interactions. In this paper, we model group dynamics using a network of semi-coupled oscillators to investigate how differences in activity schedules impact social cohesion and fragmentation. By introducing parameters for social “stickiness” (interaction strength) and activity synchronization, we simulate group behavior across varying conditions. Our findings reveal that, mathematically, cohesive groups can fragment when individual schedules diverge beyond critical thresholds, and that increasing social stickiness mitigates this effect. We explore these dynamics in the context of group size, subgroup formation, and coupling parameters, drawing parallels to network cohesion and fragmentation in human and artificial social systems. These results highlight the role of synchronization in maintaining stable social structures and suggest future avenues for empirical validation and application in broader social network contexts.