Dynamic Social Networks: Modeling Trust, Shocks and Hype

The lecture is focused on Dynamic Social Networks. In the first part, it presents an overview of the interdisciplinarity of the research issue by discussing some relevant contributions that researchers from different scientific areas have produced, from Economy to Sociology, Phisycs, Computer Sciance and Engineering The second part is dedicated to the research work that the speakers are developing at the Dept. of Information Technologies of the University of Milan. Social networks have been recognized since long as having specific topological and structural characteristics, which distinguish them from other network types widely studied in the literature. Assortative degree mixing and high clustering are two of the most notable among the others. Moreover, dynamic models of social networks study emergent behaviors of the complex system, whose dynamics is typically characterized by non-linearity, feedbacks and cascade effects. The University of Milan research group has tackled, in particular, the problem of modeling the knowledge diffusion in a social network, analyizing the results obtained through simulations. The work has been focused on the study of emergent network topologies, on trust and communication flow trhough the network, and on the definition of self-organizing mechanisms for mitigating hype effects.