Opinion formation in a locally interacting community with recommender
Simone Santini

TL;DR
This paper models opinion formation in communities with local interactions and examines how recommender systems influence opinion dynamics, showing that recommendations can homogenize opinions and potentially bias community consensus.
Contribution
It introduces a kinetic exchange-based model with local interactions and analyzes the impact of recommender systems on opinion symmetry and percolation effects.
Findings
Limited interaction range prevents symmetry breaking and percolation.
Recommender systems restore symmetry breaking and percolation effects.
Recommenders can bias community opinions towards a dominant view.
Abstract
We present a user of model interaction based on the physics of kinetic exchange, and extend it to individuals placed in a grid with local interaction. We show with numerical analysis and partial analytical results that the critical symmetry breaking transitions and percolation effects typical of the full interaction model do not take place if the range of interaction is limited, allowing for the co-existence of majorty and minority opinions in the same community. We then introduce a peer recommender system in the model, showing that, even with very local iteraction and a small probability of appeal to the recommender, its presence is sufficient to make both symmetry breaking and percolation reappear. This seems to indicate that one effect of a recommendation system is to uniform the opinions of a community, reducing minority opinions or making them disappear. Although the recommender…
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
