Understanding opinion and language dynamics using massive data

Big Data technologies are changing the informational environment in which people act, merging behavior and decision-making processes of social actors. Based on traces left by social media, we will study emerging patterns in social actions, focusing on opinion diffusion and language evolution. The following questions will guide our research: How can relevant information be obtained from Big Data and be used to elaborate explanatory models of social actions? What are the ethical consequences of the application of Big Data in the study of human actions? Two databases are selected: The New York Times collection, a traditional journal, and a collection of political tweets from Twitter, a newer online medium. Our team, with expertise in Data Science, Physics, Linguistics, Philosophy and Law aims to develop an interdisciplinary view of the relation between information patterns in Big Data and the dynamics of social actions, bridging the social and the natural sciences.

Principal Investigators

Maria Eunice Quilici Gonzalez, Universidade Estadual Paulista, Brazil, FAPESP (USD 100,000)
José Ignacio Alvarez Hamelin, Universidad de Buenos Aires, Argentina, MINCyT (ARS 40,000)
Laura Hernandez, Université de Cergy-Pontoise, France, ANR (EUR 179,712)