In social networks, resource sharing behaviors always take place in groups of individuals and rely on voluntary cooperation. In this work, first, a multi-player donor recipient game in which strategies describe individuals’ varying degrees of willingness to share resources is formulated, instead of using the limited binary decisions (e.g. share or not share) in a classical donor-recipient game. Second, the evolutionary dynamics of individual strategies are explored under the influence of two contribution-based resource allocation mechanisms: the total contribution-based allocation mechanism (TCAM) and the direct contribution-based allocation mechanism (DCAM). The results indicate that the network is dominated by the full-cooperation strategy when the cost-to-benefit ratio of resources is not too large and the DCAM is more effective than TCAM. Furthermore, the underlying reason why some strategies with higher sharing willingness can coexist in specific situations, is also explained in detail by leveraging macroscopic and microscopic perspective analysis. Finally, the influences of slandering and whitewashing behaviors conducted by a few malicious individuals on the allocation mechanisms are also studied. Current research will offer new insights into understanding the influence and optimizing the resource allocation policies in social networks.
Evolutionary dynamics of individual strategies and game environments in the framework of feedback control
