González-Bailón, Sandra
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Publication The Dynamics of Information-Driven Coordination Phenomena: A Transfer Entropy Analysis(2016-04-01) Borge-Holthoefer, Javier; Perra, Nicola; Goncalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, AlessandroData 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.Publication Automated Content Analysis of Online Political Communication(2015-01-01) Gonález-Bailón, Sandra; Petchler, RossPublication Online Social Networks and Bottom-Up Politics(2014-01-01) González-Bailón, SandraPublication The Emergence of Roles in Large-Scale Networks of Communication(2014-11-07) González-Bailón, Sandra; Wang, Ning; Borge-Holthoefer, JavierCommunication through social media mediates coordination and information diffusion across a range of social settings. However, online networks are large and complex, and their analysis requires new methods to summarize their structure and identify nodes holding relevant positions. We propose a method that generalizes the sociological theory of brokerage, originally devised on the basis of local transitivity and paths of length two, to make it applicable to larger, more complex structures. Our method makes use of the modular structure of networks to define brokerage at the local and global levels. We test the method with two different data sets. The findings show that our approach is better at capturing role differences than alternative approaches that only consider local or global network features.Publication Big Data and the Fabric of Human Geography(2013-01-01) González-Bailón, SandraDigital data tracking what we do, the time and place of our actions, and the chains of interdependence that link those actions together, help us draw a richer picture of human geography as it unfolds in its multiple layers. This commentary briefly illustrates the type of maps and models we can build with that data as well as some important challenges that arise from their complexity and unsolved validity concerns.Publication Social Science in the Era of Big Data(2013-01-01) Gonález-Bailón, SandraDigital technologies keep track of everything we do and say while we are online, and we spend online an increasing portion of our time. Databases hidden behind web services and applications are constantly fed with information of our movements and communication patterns, and a significant dimension of our lives, quantified to unprecedented levels, gets stored in those vast online repositories. This article considers some of the implications of this torrent of data for social science research, and for the types of questions we can ask of the world we inhabit. The goal of the article is twofold: to explain why, in spite of all the data, theory still matters to build credible stories of what the data reveal; and to show how this allows social scientists to revisit old questions at the intersection of new technologies and disciplinary approaches. The article also considers how Big Data research can transform policymaking, with a focus on how it can help us improve communication and governance in policy-relevant domains.Publication Diffusion Dynamics With Changing Network Composition(2013-01-01) Baños, Raquel A; Borge-Holthoefer, Javier; Wang, Nang; Moreno, Yamir; González-Bailón, SandraWe analyze information diffusion using empirical data that tracks online communication around two instances of mass political mobilization that took place in Spain in 2011 and 2012. We also analyze protest-related communications during the year that elapsed between those protests. We compare the global properties of the topological and dynamic networks through which communication took place, as well as local changes in network composition. We show that changes in network structure underlie aggregated differences on how information diffused: an increase in network hierarchy is accompanied by a reduction in the average size of cascades. The increasing hierarchy affects not only the underlying communication topology but also the more dynamic structure of information exchange; the increase is especially noticeable amongst certain categories of nodes (or users). Our findings suggest that the relationship between the structure of networks and their function in diffusing information is not as straightforward as some theoretical models of diffusion in networks imply.Publication Seminar on "The Emergence of Roles in Large-Scale Networks of Communication"(2014-09-01) González-Bailón, SandraCommunication through social media is becoming more prevalent in dynamics of coordination and information diffusion. However, online networks are so large and complex that we require new methods to summarize their structure and identify nodes holding relevant positions. We propose a method that generalizes the sociological theory of brokerage, originally devised on the basis of local transitivity and paths of length two, to make it applicable to larger, more complex structures. Our method makes use of the modular structure of networks to define brokerage at the local and global levels. The findings show that the method is better able to capture differences in communication dynamics than alternative approaches that only consider local or global network features.Publication ¿SOCIEDADES ARTIFICIALES? Una introducción a la simulación social(2004-09-01) Gonález-Bailón, SandraThese lines have a twofold objective: to introduce social simulation as a technique of analysis, and to offer a view of its uses and possibilities. The article starts with a couple of examples aimed to illustrate the practice of simulation. The methodological aspects associated to it are then exposed to, finally, highlight the pros (and cons) of its use. The aim of social simulation is the same as that of statistical equations and ideal types: to generate models of the social reality that help us to build or validate theories about its regularities. What turns social simulation into an innovative analytical strategy is not its objectives but rather its means: programming algorithms that contain the behavioural rules of agents that interact among them and with their environment. The advantages of social simulation are not only experimental but also, and specially, theoretic: it allows the search of the mechanisms that statistical models cannot provide.Publication Semantic Networks and Applications in Public Opinion Research(2018-01-01) Yang, Sijia; González-Bailón, Sandra