Analysis and control of multi-leveled opinions spreading in social networks

Vineeth Varma (1) , Irinel-Constantin Morarescu (1) , Yezekael Hayel (2)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 LIA - Laboratoire Informatique d'Avignon

This paper proposes and analyzes a stochastic multi-agent opinion dynamics model. We are interested in a multi-leveled opinion of each agent which is randomly influenced by the binary actions of its neighbors. It is shown that, as far as the number of agents in the network is finite, the model asymptotically produces consensus. The consensus value corresponds to one of the absorbing states of the associated Markov system. However, when the number of agents is large, we emphasize that partial agreements are reached and these transient states are metastable, i.e., the expected persistence duration is arbitrarily large. These states are characterized using an N-intertwined mean field approximation (NIMFA) for the Markov system. Moreover we analyze a simple and easily implementable way of controlling the opinion in the network. Numerical simulations validate the proposed analysis.

Mots clés: Opinion dynamics; Social computing and networks; Markov chains; agent based models

Domaines: Automatique

Vineeth Varma, Irinel-Constantin Morarescu, Yezekael Hayel. Analysis and control of multi-leveled opinions spreading in social networks. American Control Conference, ACC 2018, Jun 2018, Milwaukee, WI, United States. ⟨hal-01756892⟩