Opinion dynamics on social networks: from models to empirical validation

The growing abundance of social media data is creating unprecedented opportunities to understand how opinions form and evolve in communities of individuals, and also to what extent they are shaped by social interactions.For properly investigating opinion dynamics, however, we need (i) mathematical models representing the complex dynamical phenomena occurring on social networks, and (ii) methods for validating/invalidating the models on real datasets.

The proposal deals with both research directions, with the overarching goal to attain a better understanding of certain collecting behaviors occurring on social networks.

More in detail, we plan to study the following aspects: (1): Understand when social interactions can induce wisdom of crowd effects in opinion dynamics; (2): Investigate what factors, such as opinion polarization or clustering, can hamper wisdom of crowd effects and how; (3): Study how influence propagates in opinion dynamics using a recently developed game-theoretical framework for ´social power´ maximization on social networks; (4): Exploit the methods and models considered in the project (such as wisdom of crowd, antagonism, etc.) for developing algorithms for collective behavior and decision-making in multi-agent systems in contexts other than opinion dynamics.