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arXiv · 2501.13215

Voter model can accurately predict individual opinions in online populations

Antoine Vendeville
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Abstract

Models of opinion dynamics describe how opinions are shaped in various environments. While these models are able to replicate general opinion distributions observed in real-world scenarios, their capacity to align with data at the user level remains mostly untested. We evaluate the capacity of the multi-state voter model with zealots to capture individual opinions in a fine-grained Twitter dataset collected during the 2017 French Presidential elections. Our findings reveal a strong correspondence between individual opinion distributions in the equilibrium state of the model and ground-truth political leanings of the users. Additionally, we demonstrate that discord probabilities accurately identify pairs of like-minded users. These results emphasize the validity of the voter model in complex settings, and advocate for further empirical evaluations of opinion dynamics models at the user level.

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Antoine Vendeville. 2025-01-22. Voter model can accurately predict individual opinions in online populations. https://doi.org/10.1103/physreve.111.064310

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