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An evidence-accumulating drift–diffusion model of competing information spread on networks

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  • Corsin, Julien
  • Zino, Lorenzo
  • Ye, Mengbin

Abstract

In this paper, we propose an agent-based model of information spread, grounded on psychological insights on the formation and spread of beliefs. In our model, we consider a network of individuals who share two opposing types of information on a specific topic (e.g., pro- vs. anti-vaccine stances), and the accumulation of evidence supporting either type of information is modelled by means of a drift–diffusion process. After formalising the model, we put forward a campaign of Monte Carlo simulations to identify population-wide behaviours emerging from agents’ exposure to different sources of information, investigating the impact of the number and persistence of such sources, and the role of the network structure through which the individuals interact. We find similar emergent behaviours for all network structures considered. When there is a single type of information, the main observed emergent behaviour is consensus. When there are opposing information sources, both consensus or polarisation can result; the latter occurs if the number and persistence of the sources exceeds a threshold value identified in the simulations. Importantly, we find the emergent behaviour is mainly influenced by how long the information sources are present for, as opposed to how many sources there are.

Suggested Citation

  • Corsin, Julien & Zino, Lorenzo & Ye, Mengbin, 2025. "An evidence-accumulating drift–diffusion model of competing information spread on networks," Chaos, Solitons & Fractals, Elsevier, vol. 192(C).
  • Handle: RePEc:eee:chsofr:v:192:y:2025:i:c:s0960077924014875
    DOI: 10.1016/j.chaos.2024.115935
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    1. repec:plo:pone00:0175799 is not listed on IDEAS
    2. Zhang, Wei & Brandes, Ulrik, 2023. "Conformity versus credibility: A coupled rumor-belief model," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    3. Lu, Peng & Yang, Hou & Li, Mengdi & Zhang, Zhuo, 2021. "The sandpile model and empire dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    4. Mengbin Ye & Lorenzo Zino & Žan Mlakar & Jan Willem Bolderdijk & Hans Risselada & Bob M. Fennis & Ming Cao, 2021. "Collective patterns of social diffusion are shaped by individual inertia and trend-seeking," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    5. Bulai, Iulia Martina & Sensi, Mattia & Sottile, Sara, 2024. "A geometric analysis of the SIRS compartmental model with fast information and misinformation spreading," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    6. Nekovee, M. & Moreno, Y. & Bianconi, G. & Marsili, M., 2007. "Theory of rumour spreading in complex social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 457-470.
    7. Mohammadi, Sohameh & Nadimi-Shahraki, Mohammad H. & Beheshti, Zahra & Zamanifar, Kamran, 2024. "Improved information diffusion models based on a new two-sided sign-aware matching framework in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    8. Daniel A Sprague & Thomas House, 2017. "Evidence for complex contagion models of social contagion from observational data," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-12, July.
    9. Acemoglu, Daron & Ozdaglar, Asuman & ParandehGheibi, Ali, 2010. "Spread of (mis)information in social networks," Games and Economic Behavior, Elsevier, vol. 70(2), pages 194-227, November.
    10. Bjarke Mønsted & Piotr Sapieżyński & Emilio Ferrara & Sune Lehmann, 2017. "Evidence of complex contagion of information in social media: An experiment using Twitter bots," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-12, September.
    11. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
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