Who should fight the spread of fake news?

This study investigates who should bear the responsibility of combating the spread of misinformation in social networks. Should that be the online platforms or their users? Should that be done by debunking the ‘fake news’ already in circulation or by investing in preemptive efforts to prevent their diffusion altogether? We seek to answer such questions in a stylized opinion dynamics framework, where agents in a network aggregate the information they receive from peers and/or from influential external sources, with the aim of learning a ground-truth among a set of competing hypotheses. In most cases, we find centralized sources to be more effective at combating misinformation than distributed ones, suggesting that online platforms should play an active role in the fight against fake news. In line with literature on the ‘backfire effect’, we find that debunking in certain circumstances can be a counterproductive strategy, whereas some targeted strategies (akin to ‘deplatforming’) and/or preemptive campaigns turn out to be quite effective. Despite its simplicity, our model provides useful guidelines that could inform the ongoing debate on online disinformation and the best ways to limit its damaging effects.

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Publication Details

Journal
Physica A Statistical Mechanics and its Applications
Published
2026-02-21
DOI
https://doi.org/10.1016/j.physa.2026.131396
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
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article

Who should fight the spread of fake news?

Giacomo Livan, Diana Riazi
Physica A Statistical Mechanics and its Applications
Misinformation and Its Impacts
article

Who should fight the spread of fake news?

Giacomo Livan, Diana Riazi
article en

Abstract

This study investigates who should bear the responsibility of combating the spread of misinformation in social networks. Should that be the online platforms or their users? Should that be done by debunking the ‘fake news’ already in circulation or by investing in preemptive efforts to prevent their diffusion altogether? We seek to answer such questions in a stylized opinion dynamics framework, where agents in a network aggregate the information they receive from peers and/or from influential external sources, with the aim of learning a ground-truth among a set of competing hypotheses. In most cases, we find centralized sources to be more effective at combating misinformation than distributed ones, suggesting that online platforms should play an active role in the fight against fake news. In line with literature on the ‘backfire effect’, we find that debunking in certain circumstances can be a counterproductive strategy, whereas some targeted strategies (akin to ‘deplatforming’) and/or preemptive campaigns turn out to be quite effective. Despite its simplicity, our model provides useful guidelines that could inform the ongoing debate on online disinformation and the best ways to limit its damaging effects.

Physica A Statistical Mechanics and its ApplicationsVol. 688
University of Pavia (IT), Istituto Nazionale di Fisica Nucleare, Sezione di Pavia (IT), University College London (GB)
Reduced inequalities
Openalex Percentile: Top 53%
Misinformation and Its Impacts
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Who should fight the spread of fake news? — Giacomo Livan, Diana Riazi · Physica A Statistical Mechanics and its Applications (2026) | TGRS Research Map | TGRS