Link overlap influences opinion dynamics on multiplex networks: spin model approach
Cook Hyun Kim, Minjae Jo, J. S. Lee, G. Bianconi, B. Kahng

TL;DR
This paper investigates how link overlap in multiplex social networks influences opinion dynamics, revealing that multilink properties significantly affect phase transitions in a spin model of opinion formation.
Contribution
It introduces the Ashkin-Teller spin model to study opinion dynamics on multiplex networks with link overlap, highlighting the impact of multilink statistics on phase transitions.
Findings
Link overlap significantly affects opinion formation patterns.
The model exhibits various phase transitions, including continuous and discontinuous.
Multidegree distribution influences the nature of phase transitions.
Abstract
Consider a multiplex network formed by two layers indicating social interactions: the first layer is a friendship network and the second layer is a network of business relations. In this duplex network each pair of individuals can be connected in different ways: they can be connected by a friendship but not connected by a business relation, they can be connected by a business relation without being friends, or they can be simultaneously friends and in a business relation. In the latter case we say that the links in different layers overlap. These three types of connections are called multilinks and the multidegree indicates the sum of multilinks of a given type that are incident to a given node. Previous models of opinion formation on multilayer networks have mostly neglected the effect of link overlap. Here we show that link overlap can have important effects in opinion formation.…
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 · Complex Network Analysis Techniques · Complex Systems and Time Series Analysis
