Opinion dynamics in social networks

In the last years, an increasing attention was reserved by research community to the understanding and the analysis of collective social belief dynamics over networks. This interest has been stimulated by the growing awareness of the fundamental role that social networks and media may play in the formation and diffusion of opinions/beliefs. For example, it is widely recognized that social media have played a fundamental role in several recent political events, such as, the “Arabian Spring“ or the last US presidential campaign. Moreover, the availability of large amount of social data generated by users have attracted  he interest of enterprises and government agencies, which envision opportunities of exploiting such data to timely get important real-time insights on evolution of trends/tastes/opinions in the society.   Our activity aims to develop, analyse  and validate analytical models representing opinion dynamics, In particular we propose  a fairly general dynamical model of social interactions, which captures all the main features exhibited by a social system. For such model, by embracing a mean field approach, we derive a diffusion differential equation that represents asymptotic belief dynamics, as the number of users grows large. Our goal is to analyze the steady-state behavior as well as the time dependent (transient) behavior of the system.

ERC Sector:

  • PE7_3 Simulation engineering and modelling

Keywords:

  • Partial differential equations
  • Stochastic processes
  • Opinion dynamic
  • Epidemic processes

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