Reaction times for user behavior models in microblogging Online Social Networks

Abstract

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 multiagent 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. Copyright 2013 ACM.