We study the evolutionary Prisoner’s Dilemma on two social networks substrates obtained from actual relational data. We find very different cooperation levels on each of them that cannot be easily understood in terms of global statistical properties of both networks. We claim that the result can be understood at the mesoscopic scale, by studying the community structure of the networks. We explain the dependence of the cooperation level on the temptation parameter in terms of the internal structure of the communities and their interconnections. We then test our results on community-structured, specifically designed artificial networks, finding a good agreement with the observations in both real substrates. Our results support the conclusion that studies of evolutionary games on model networks and their interpretation in terms of global properties may not be sufficient to study specific, real social systems. Further, the study allows us to define new quantitative parameters that summarize the mesoscopic structure of any network: intra-community heterogeneity (IH) and inter-community connectivity (IC). These mesoscopic features along with the prominent role played by hubs allow us to understand the origin of the different results observed in the two networks. In addition, the community perspective may be helpful to interpret the origin and behavior of existing networks as well as to design structures that show resilient cooperative behavior. Our main conclusion, namely that cooperation in real social networks is a complex issue depending on the combination of the effects of several structural features, has far-reaching implications: subsequent studies on these issues should from now on be carried out on a case by case basis, and should involve a careful analysis at a mesoscopic (community) level.

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