Date : December, 3th 2013 at 15:00
Room : IXXI
Since the 19th century many scholars have pondered on the existence of quantitative laws that describe the collective behaviour of a large number of people. Although fields like statistics and sociometry have long studied the dynamical regularities and structural properties of social systems, it is only recently that the description of society has been approached within the framework of statistical physics. The fast development of such ‘physics of social atoms’ is mainly due to the current availability of large datasets on online human behaviour, and includes a myriad of simplified mathematical models aimed at quantifying and predicting social interactions.
In this talk I will present a couple of models for the dynamics of opinion and social conflict, both motivated and qualitatively validated by empirical data. The first model explores the coupled evolution of social network structure and individual opinions regarding a controversial topic, and emulates the segregation of opposing opinion groups seen in a controlled experiment where students discuss drug-legalisation issues. The second model describes the production of a common product by collaborating individuals with diverse opinions, characterising different regimes of conflict that match editorial activity in Wikipedia articles. These results offer an inkling on the promising field of data-driven social dynamics, otherwise known as computational social science.