title: The dynamics of information-driven coordination phenomena: A transfer entropy analysis.
abstract: 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.
authors.affiliation: Qatar Computing Research Institute, Hamad Bin Khalifa University, P.O. Box 5825 Doha, Qatar.
authors.forename: Javier
authors.identifier: 0000-0001-9036-8463
authors.initials: J
authors.lastname: Borge-Holthoefer
authors.affiliation: Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, MA 02115, USA.
authors.forename: Nicola
authors.initials: N
authors.lastname: Perra
authors.affiliation: Aix-Marseille Université, Université de Toulon, CNRS, CPT, UMR 7332, 13288 Marseille, France.
authors.forename: Bruno
authors.initials: B
authors.lastname: Gonçalves
authors.affiliation: Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104, USA.
authors.forename: Sandra
authors.identifier: 0000-0001-5644-3749
authors.initials: S
authors.lastname: González-Bailón
authors.affiliation: Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, 43007 Tarragona, Spain.
authors.forename: Alex
authors.identifier: 0000-0003-0937-0334
authors.initials: A
authors.lastname: Arenas
authors.affiliation: Department of Theoretical Physics, Faculty of Sciences, University of Zaragoza, 50009 Zaragoza, Spain.; Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, 50018 Zaragoza, Spain.; Institute for Scientific Interchange, 10126 Torino, Italy.
authors.forename: Yamir
authors.initials: Y
authors.lastname: Moreno
authors.affiliation: Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, MA 02115, USA.; Institute for Scientific Interchange, 10126 Torino, Italy.; Institute for Quantitative Social Sciences at Harvard University, Cambridge, MA 02138, USA.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Vespignani
mesh_terms: D000465:Algorithms; D019277:Entropy; D034441:Heterogeneous-Nuclear Ribonucleoproteins; D006801:Humans; D008962:Models, Theoretical; D017711:Nonlinear Dynamics; D061108:Social Media
chemical_list: D034441:Heterogeneous-Nuclear Ribonucleoproteins
keywords: collective phenomena; dynamical transitions; transfer entropy