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Opinion Dynamics on Correlated Subjects in Social Networks

Academic Article
Publication Date:
2019
abstract:
Understanding the evolution of collective beliefs is of critical importance to get insights on the political trends as well as on social tastes and opinions. In particular, it is pivotal to develop analytical models that can predict the beliefs dynamics and capture the interdependence of opinions on different subjects. In this paper we tackle this issue also accounting for the individual endogenous process of opinion evolution, as well as repulsive interactions between individuals' opinions that may arise in the presence of an adversarial attitude of the individuals. Using a mean field approach, we characterize the time evolution of opinions of a large population of individuals through a multidimensional Fokker-Planck equation, and we identify the conditions under which stability holds. Finally, we derive the steady-state opinion distribution as a function of the individuals' personality and of the existing social interactions. Our numerical results show interesting dynamics in the collective beliefs of different social communities, and they highlight the effect of correlated subjects as well as of individuals with an adversarial attitude.
Iris type:
01.01 Articolo in rivista
Keywords:
Mathematical model; Social network services; Stability analysis; Numerical stability; Adaptation models; Sociology; Statistics
List of contributors:
Chiasserini, CARLA FABIANA; Nordio, Alessandro; Tarable, Alberto
Authors of the University:
NORDIO ALESSANDRO
TARABLE ALBERTO
Handle:
https://iris.cnr.it/handle/20.500.14243/361438
Published in:
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
Journal
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