Abstract: Modern social systems such as Twitter expose digital traces of social discourse with an unprecedented degree of resolution of individual behaviors. They offer an opportunity to investigate both individual and collective behavioral patterns and to disentangle the temporal, spatial and topical aspects of human activity.
A large survey of online exchanges or conversations on Twitter, collected across six months involving 1.7 million individuals is used to study how individuals manage their social relations. Two main features are observed:
1. Social interaction strength is highly dependent of the number of connections, corroborating Dunbar’s Social Brain theory. A simple model shows how limited individual capacity for social interaction is enough to qualitatively reproduce the features observed.
2. Users display extremely diverse activity levels that follow a broad tailed distribution. We construct an activity driven model that is capable of encoding the instantaneous time description of social network dynamics. Within this framework, highly dynamical networks can be described analytically, providing a powerful tool for the analysis of social phenomena occurring over time-varying networks.
Finally, we focus on Twitter activity surrounding American Idol voting as minimal and simplified version of complex societal phenomena such as political elections, and show that the volume of information available in online systems permits the real time gathering of quantitative indicators anticipating the future unfolding of opinion formation events.
Time & place:
Monday 24 September at 11:00-12:00
Building 305, Seminar room 053