Fast but multi-partisan: Bursts of communication increase opinion diversity in the temporal Deffuant model
Fatemeh Zarei, Yerali Gandica, Luis Enrique Correa Rocha

TL;DR
This paper introduces a temporal version of the Deffuant opinion model showing that bursty social interactions promote opinion diversity and prevent polarization, especially in online social networks with low clustering.
Contribution
It develops a temporal Deffuant model demonstrating how burstiness and network clustering influence opinion diversity and polarization, highlighting the role of interaction timing.
Findings
Burstiness prevents consensus and polarization.
Opinion diversity increases with burstiness and low tolerance.
Online social networks are more prone to polarization due to low clustering.
Abstract
Human interactions create social networks forming the backbone of societies. Individuals adjust their opinions by exchanging information through social interactions. Two recurrent questions are whether social structures promote opinion polarisation or consensus in societies and whether polarisation can be avoided, particularly on social media. In this paper, we hypothesise that not only network structure but also the timings of social interactions regulate the emergence of opinion clusters. We devise a temporal version of the Deffuant opinion model where pairwise interactions follow temporal patterns and show that burstiness alone is sufficient to refrain from consensus and polarisation by promoting the reinforcement of local opinions. Individuals self-organise into a multi-partisan society due to network clustering, but the diversity of opinion clusters further increases with…
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 · Social Capital and Networks
