The dynamics of information-driven coordination phenomena: A transfer entropy analysis

J. Borge-Holthoefer, N. Perra, B. Gonçalves, S. González-Bailón, A. Arenas, Y. Moreno, and A. Vespignani
Science Advances
2 (4), e1501158 (2016)
April 1, 2016


Data from social media provide unprecedented opportunities to investigate the processes that  govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and  structural signatures typical of collective social events as they arise and  gain prominence. We use the symbolic transfer entropy analysis of  microblogging time series to extract directed networks of influence among  geolocalized subunits in social systems. This methodology captures the  emergence of system-level dynamics close to the onset of socially relevant  collective phenomena. The framework is validated against a detailed empirical  analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of  information-driven collective phenomena. Furthermore, our approach identifies  an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective  phenomena can be represented as endogenously driven structural transitions of  the information transfer network. This study provides results that can help  define models and predictive algorithms for the analysis of societal events  based on open source data.

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