Kenneth Frank and Ran Xu
London E1W 1YW, UK
Portland, ME 04101
2nd floor
11th floor
Boston, MA 02115
2nd floor
London E1W 1LP, UK
Talk recording
Although network structures shape diffusion and ultimately systemic performance, the underlying dynamics generating different network structures during diffusion are not well understood. To explore these dynamics we present a set of models driven by a single motivation for generalized balance – the inclination to align the attributes of one’s network members with one’s own attributes either by adopting the attributes of network members or by selecting to interact with similar others. Simulations show that the models generate core-periphery network structures for low levels of generalized balance and polarization (modularity) for high levels of generalized balance. Moreover, the more network members influence one another the more the transition from core-periphery to polarization is delayed but then drastic, in the extreme creating a phase transition. Thus, the rate of influence amplifies the attractiveness of a particular state of the system. The results match transitions in scholarly citation networks and terrorist networks.