Analyzing dynamical social interactions as temporal networks

摘要

Digital records of social interactions collected via online communication tools and sensing devices add a new dimension to social network analysis: time. Universal patterns in social temporal networks, such as heterogeneity in interevent times, have been unveiled on the basis of empirical data analysis. In addition, these temporal patterns exhibit considerable impact on dynamical processes such as disease spreading and tie formation. In this paper, recent advances in social temporal network analysis will be presented and a future perspective will be discussed.