Tolerance-based interaction: A new model targeting opinion formation and diffusion in social networks
- Published
- Accepted
- Subject Areas
- Network Science and Online Social Networks, Scientific Computing and Simulation, Social Computing
- Keywords
- social networks, opinion diffusion, phase transition, discrete event simulation, tolerance
- Copyright
- © 2015 Topirceanu et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Tolerance-based interaction: A new model targeting opinion formation and diffusion in social networks. PeerJ PrePrints 3:e1322v1 https://doi.org/10.7287/peerj.preprints.1322v1
Abstract
One of the main motivations behind social network analysis is the quest for understanding opinion formation and diffusion. Previous models have limitations, as they typically assume opinion interaction mechanisms based on thresholds which are either fixed or evolve according to a random process that is external to the social agent. Indeed, our empirical analysis on large real-world datasets such as Twitter, Meme Tracker, and Yelp, uncovers previously unaccounted for dynamic phenomena at population-level, namely the existence of distinct opinion formation phases and social balancing. We also reveal that a phase transition from an erratic behavior to social balancing can be triggered by network topology and by the ratio of opinion sources. Consequently, in order to build a model that properly accounts for these phenomena, we propose a new (individual-level) opinion interaction model based on tolerance. As opposed to the existing opinion interaction models, the new tolerance model assumes that individual's inner willingness to accept new opinions evolves over time according to basic human traits. Finally, by employing discrete event simulation on diverse social network topologies, we validate our opinion interaction model and show that, although the network size and opinion source ratio are important, the phase transition to social balancing is mainly fostered by the democratic structure of the small-world topology.
Author Comment
This is a submission to PeerJ Computer Science for review.