ArticleScientific reports2022
A general framework to link theory and empirics in opinion formation models.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Social Contagion in COVID-19 Discussions Within the Belgian Reddit Community: Statistical and Modeling Study.Journal of medical Internet research · 2026Article
- Control over Recommendation Algorithms in Heterogeneous Modular Systems with Dynamic Opinions.Entropy (Basel, Switzerland) · 2026Article
- Speaking of Opinions: Comparing Approaches to Modelling Opinion Manipulation.La matematica · 2026Review
- Detailed-level modelling of influence spreading on complex networks.Scientific reports · 2024Article
- Graphical analysis of agent-based opinion formation models.PloS one · 2024Article
- Probabilistic analysis of agent-based opinion formation models.Scientific reports · 2023Article
- Health behavior in Russia during the COVID-19 pandemic.Frontiers in public health · 2023Article
- Vanishing Opinions in Latané Model of Opinion Formation.Entropy (Basel, Switzerland) · 2022Article
- Opinion Dynamics and Unifying Principles: A Global Unifying Frame.Entropy (Basel, Switzerland) · 2022Article
- Dynamic Parameter Calibration Framework for Opinion Dynamics Models.Entropy (Basel, Switzerland) · 2022Article
- A framework to analyze opinion formation models.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce a minimal opinion formation model that is quite flexible and can reproduce a wide variety of the existing micro-influence assumptions and models. The model can be easily calibrated on real data, upon which it imposes only a few requirements. From this perspective, our model can be considered as a bridge, connecting theoretical studies on opinion formation models and empirical research on social dynamics. We investigate the model analytically by using mean-field approximation and numerically via Monte Carlo simulations. Our analysis is exemplified by recently reported empirical data drawn from an online social network. We demonstrate that the model calibrated on these data may reproduce fragmented and polarizing social systems. Furthermore, we manage to generate an artificial society that features properties quantitatively and qualitatively similar to those observed empirically at the macro scale. This ability became possible after we had advanced the model with two important communication features: selectivity and personalization algorithms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.