Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We consider two fundamental forces that can drive the diffusion of an innovation on a network. The first of these forces is potential maximization, a method of aggregating payoff incentives of players under individual agency. Potential maximization is related to the graph theoretic property of close-knittedness (Young, 2011). The second force is collective agency, under which sets of players decide together on whether to adjust their strategies. Collective agency is shown to be related to the graph theoretic property of cohesion (Morris, 2000). We compare the relative strengths of these forces under (i) different payoff specifications in coordination games and (ii) different network structures.