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

Fuente: arXiv
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Autori principali: Corsin, Julien, Zino, Lorenzo, Ye, Mengbin
Natura: Preprint
Pubblicazione: 2024
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author Corsin, Julien
Zino, Lorenzo
Ye, Mengbin
author_facet Corsin, Julien
Zino, Lorenzo
Ye, Mengbin
contents 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 some threshold values. 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.
format Preprint
id arxiv_https___arxiv_org_abs_2408_12127
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An evidence-accumulating drift-diffusion model of competing information spread on networks
Corsin, Julien
Zino, Lorenzo
Ye, Mengbin
Physics and Society
Social and Information Networks
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 some threshold values. 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.
title An evidence-accumulating drift-diffusion model of competing information spread on networks
topic Physics and Society
Social and Information Networks
url https://arxiv.org/abs/2408.12127