Discovering the Dynamics in a Social Memory Network

A social network consists of events and individuals, in which the events denote the activities happening in the system and the individuals denotes the peoples who are attracted into the activities. A memory feature exists in a dynamic social network which leads to the decay of the event attraction, and further influences the structure and the dynamics of the network. In the paper, an agent model for a social memory network is built and implemented. The simulation result reveals the dynamics of the average life span of events. The result also discovers how a social network with a small "diameter" and a large clustering coefficient evolves. The model is validated with the empirical data from USTC bulletin board system (BBS).