MITIGATING DISINFORMATION IN SOCIAL NETWORKS THROUGH NOISE

Diana Riazi () and Giacomo Livan
Additional contact information
Diana Riazi: Department of Computer Science, University College London, 66-72 Gower Street, London WC1E 6EA, UK
Giacomo Livan: Department of Computer Science, University College London, 66-72 Gower Street, London WC1E 6EA, UK2Department of Physics, University of Pavia, Via Bassi 6, Pavia 27100, Italy3INFN, Sezione di Pavia, Via Bassi 6, Pavia 27100, Italy

Advances in Complex Systems (ACS), 2025, vol. 28, issue 04, 1-12

Abstract: An abundance of literature has shown that the injection of noise into complex socio-economic systems can improve their resilience. This study aims to understand whether the same applies in the context of information diffusion in social networks. Specifically, we aim to understand whether the injection of noise in a social network of agents seeking to uncover a ground truth among a set of competing hypotheses can build resilience against disinformation. We implement two different stylized policies to inject noise in a social network, i.e. via random bots and via randomized recommendations, and find both to improve the population’s overall belief in the ground truth. Notably, we find noise to be as effective as debunking when disinformation is particularly strong. On the other hand, such beneficial effects may lead to a misalignment between the agents’ privately held and publicly stated beliefs, a phenomenon which is reminiscent of cognitive dissonance.

Keywords: Opinion dynamics; misinformation spread; complex systems (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219525925500079
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:28:y:2025:i:04:n:s0219525925500079

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219525925500079

Access Statistics for this article

Advances in Complex Systems (ACS) is currently edited by Frank Schweitzer

More articles in Advances in Complex Systems (ACS) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().