Opinions with few disciples can win in the dynamical directed networks: an evolutionary game perspective
Yakun Wang, Bin Wu

TL;DR
This paper models opinion formation on dynamic directed networks using an evolutionary game approach, revealing that opinions with fewer followers can dominate due to network directionality.
Contribution
It introduces a novel voter model on dynamical directed networks and links opinion invasion to emergent multi-player evolutionary games, highlighting the role of network directionality.
Findings
Opinion invasion is described by a four-player two-strategy game.
Average in(out)-degree for opinions is captured by a three-player game.
Opinions with fewer disciples can dominate in directed networks.
Abstract
The voter model on networks is crucial to understand opinion formation. Uni-directional social interactions are ubiquitous in real social networks whereas undirected interactions are intensively studied. We establish a voter model on a dynamical directed network. We show that the opinion invasion is captured by a replicator equation of an emergent four-player two-strategy game, and the average in(out)-degree for the two opinions is fully captured by an emergent three-player two-strategy game. Interestingly, it is shown that the difference between the two emergent games arises from the uni-directionality of the network. The difference implies that the opinion with a small number of disciples can take over the population for in-group bias, provided that the network is directed. Our work makes an explicit connection between opinion dynamics and evolutionary games.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOpinion Dynamics and Social Influence · Evolutionary Game Theory and Cooperation · Mathematical and Theoretical Epidemiology and Ecology Models
