Modeling and simulation of e-mail social networks: A new stochastic agent-based approach

Abstract

Understanding how the structure of a network evolves over time is one of the most interesting and complex topics in the field of social networks. In our attempt to model the dynamics of such systems, we explore an agent-based approach to model growth of email-based social networks, in which individuals establish, maintain and allow atrophy of links through contact-lists and e-mails. The model is based on the idea of common neighbors, but also on a detailed specialization of the classical preferential attachment theory, thus capturing a deeper understanding of the topology of inter-node connections. In our event-based simulation that schedules the agents¿ actions over time, the proposed model is amenable to significant efficiency improvements through an application of the Gillespie stochastic simulation schemes. Computer simulation results are used to validate the model by showing that its unique features endow it with ability to simulate real-world email networks with convincing realism.