MODASS

Temporal networks: slowing down diffusion by long lasting interactions

Abstract of the project:

The study of complex systems has attracted the interest of the scientific community from very different fields such as biology to economics, including physics. In this context, the study of social systems have played an important role. Taking as a starting point the consolidate experience of the research team, the project aims at building a line of work in the description and modeling of social systems. In particular the project proposes three lines of action: how individuals interact, when the interaction happend, and what is exchange. The 'how' refers to the plasticity of complex networks, to the structural evolution. Although the interactions are often represented by complex networks that typically add information in a temporal window, the aim is to describe the temporal evolution of the social interactions. The 'when' is referring to the fact that the actors do not interact evenly in time but the activity is described rather by bursts. The aim is to characterize the temporal correlations in human activity and determine their influence on the dynamics of competition of opinions. The 'what' questions about opinions, ie, the features that individuals interchange during the interaction. The first goal is to characterize how opinions, rumors, or fashions compete in a real social system and then, propose models that capture the results ot the characterization. To achieve these objectives, the lines of action will be developed empirically and from modeling in relation with social media and election results. The activity of users in social networks (Twitter, Flickr) will describe 'how' and 'when', ie, how the social network evolves, the patterns of user activity, and the ralationship between the activity and the position of each social network user. The use of election's results from several countries (Spain, USA) and surveys of voting intentions and mobility will allow us to answer 'how' and 'why', this is: to describe the evolution of opinion, identify local contributions -from patterns of movement between districts (commuting)- and global -from an external signal, public opinion, crisis-, and finally propose a model that captures the described behavior.