Multi-Issue Opinion Diffusion under Constraints

Sirin Botan (1) , Umberto Grandi (2, 3) , Laurent Perrussel (2, 3)

1 ILLC - Institute for Logic, Language and Computation
2 IRIT-LILaC - Logique, Interaction, Langue et Calcul
3 UT Capitole - Université Toulouse Capitole

Most existing models of opinion diffusion on networks neglect the existence of logical constraints that might correlate individual opinions on multiple issues. In this paper we study the diffusion of constrained opinions on a social network as an iterated process of aggregating neighbouring opinions. Individual views are modelled as vectors of yes/no answers to a number of propositions subject to integrity constraints, and each individual updates her opinion by looking at the aggregated opinion of her influencers. To overcome the problem of updating towards inconsistent influencing opinions, we propose a model based on individual updates on subsets of the issues of limited size called propositionwise updates. By adapting notions from the theory of boolean functions, we identify classes of integrity constraints on which propositionwise updates decrease the influence gap between nodes of the network and their influencers caused by the presence of an integrity constraint. Furthermore, we provide a detailed study of the termination of the proposed diffusion processes.

Mots clés: Boolean functions; Opinion transformation; Judgment aggregation; Social networks

Domaines: Logique en informatique [cs.LO]

Sirin Botan, Umberto Grandi, Laurent Perrussel. Multi-Issue Opinion Diffusion under Constraints. Proceedings of the 18th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), pp.828-836, 2019. ⟨hal-02435349⟩