Effect of collective influence on the evolution of cooperation in evolutionary prisoner’s dilemma games

Node centrality plays an important role in many dynamical processes taking place on complex networks. In this work, we associate the individuals’ collective influence (CI) with their strategy-updating time scales to investigate how the diverse collective influence of individuals affects the evolution of cooperation in the evolutionary prisoner’s dilemma game on scale-free networks. With the combination of time scale mechanism which bridges the feedback between strategy-updating time scale and the performance of individuals, we find that influential cooperators locating at medium- or small-degrees are able to spread their behaviors among neighbors in a more efficient way than hubs with large-degrees. Hence, collective influence with proper path length can efficiently identify influencers and may promote the emergence of cooperation on heterogeneous interaction networks.