Print Email Facebook Twitter A framework to analyze opinion formation models Title A framework to analyze opinion formation models Author Devia Pinzon, C.A. (TU Delft Team Tamas Keviczky) Giordano, G. (TU Delft Team Tamas Keviczky; Università di Trento) Date 2022 Abstract Comparing model predictions with real data is crucial to improve and validate a model. For opinion formation models, validation based on real data is uncommon and difficult to obtain, also due to the lack of systematic approaches for a meaningful comparison. We introduce a framework to assess opinion formation models, which can be used to determine the qualitative outcomes that an opinion formation model can produce, and compare model predictions with real data. The proposed approach relies on a histogram-based classification algorithm, and on transition tables. The algorithm classifies an opinion distribution as perfect consensus, consensus, polarization, clustering, or dissensus; these qualitative categories were identified from World Values Survey data. The transition tables capture the qualitative evolution of the opinion distribution between an initial and a final time. We compute the real transition tables based on World Values Survey data from different years, as well as the predicted transition tables produced by the French-DeGroot, Weighted-Median, Bounded Confidence, and Quantum Game models, and we compare them. Our results provide insight into the evolution of real-life opinions and highlight key directions to improve opinion formation models. Subject OA-Fund TU Delft To reference this document use: http://resolver.tudelft.nl/uuid:8742697e-5f20-4ebd-a5c9-284f83bbbff6 DOI https://doi.org/10.1038/s41598-022-17348-z ISSN 2045-2322 Source Scientific Reports, 12 (1) Part of collection Institutional Repository Document type journal article Rights © 2022 C.A. Devia Pinzon, G. Giordano Files PDF s41598_022_17348_z.pdf 3.26 MB Close viewer /islandora/object/uuid:8742697e-5f20-4ebd-a5c9-284f83bbbff6/datastream/OBJ/view