An agent-based approach for building complex software systems
Communications of the ACM
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The dynamics of viral marketing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
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Online Social Networks (OSNs) have, in recent years, emerged as a new way to communicate, diffuse information, coordinate people, establish relationships, among other possibilities. In this context, being able to understand and predict how users behave and developing appropriate models is a key problem to work with OSNs, concerning from marketing campaigns to social movements, for example. Twitter, for instance, was a heavily explored tool in Obama's 2012 election. In this paper, we explore Obama's Twitter network and model its users behavior, applying a stochastic multi-agent based simulation to reproduce the observed data. We study the effects of different time discretizations when applying a first order Markov Model to learn the user behavior and determine that, for Obama's egocentric network, users present a short reaction time to received messages.