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The Value of Information Searching against Fake News

2020-12-03Journal article Open access
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datacite.subject.fosCiências Naturais::Matemáticas
datacite.subject.fosCiências Naturais::Ciências Físicas
datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
dc.contributor.authorMartins, José
dc.contributor.authorPinto, Alberto
dc.date.accessioned2025-07-16T11:35:52Z
dc.date.available2025-07-16T11:35:52Z
dc.date.issued2020-12-03
dc.descriptionArticle number - 1368
dc.description.abstractInspired by the Daley-Kendall and Goffman-Newill models, we propose an Ignorant-Believer-Unbeliever rumor (or fake news) spreading model with the following characteristics: (i) a network contact between individuals that determines the spread of rumors; (ii) the value (cost versus benefit) for individuals who search for truthful information (learning); (iii) an impact measure that assesses the risk of believing the rumor; (iv) an individual search strategy based on the probability that an individual searches for truthful information; (v) the population search strategy based on the proportion of individuals of the population who decide to search for truthful information; (vi) a payoff for the individuals that depends on the parameters of the model and the strategies of the individuals. Furthermore, we introduce evolutionary information search dynamics and study the dynamics of population search strategies. For each value of searching for information, we compute evolutionarily stable information (ESI) search strategies (occurring in non-cooperative environments), which are the attractors of the information search dynamics, and the optimal information (OI) search strategy (occurring in (eventually forced) cooperative environments) that maximizes the expected information payoff for the population. For rumors that are advantageous or harmful to the population (positive or negative impact), we show the existence of distinct scenarios that depend on the value of searching for truthful information. We fully discuss which evolutionarily stable information (ESI) search strategies and which optimal information (OI) search strategies eradicate (or not) the rumor and the corresponding expected payoffs. As a corollary of our results, a recommendation for legislators and policymakers who aim to eradicate harmful rumors is to make the search for truthful information free or rewarding.eng
dc.description.sponsorshipFunding: This research was funded by LIAAD-INESC TEC and FCT Fundação para a Ciência e Tecnologia (Portuguese Foundation for Science and Technology) within project UID/EEA/50014/2019 and by National Funds through the FCT within Project “Modelling, dynamics and games”, with reference PTDC/MAT-APL/31753/2017. Acknowledgments: The authors thank the referees for their invaluable comments and suggestions.
dc.identifier.citationMartins, J., & Pinto, A. (2020). The Value of Information Searching against Fake News. Entropy, 22(12), 1368. https://doi.org/10.3390/e22121368.
dc.identifier.doi10.3390/e22121368
dc.identifier.issn1099-4300
dc.identifier.urihttp://hdl.handle.net/10400.8/13668
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI
dc.relationModelling, dynamics and games
dc.relation.hasversionhttps://www.mdpi.com/1099-4300/22/12/1368
dc.relation.ispartofEntropy
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectfake news
dc.subjectrumor spreading
dc.subjectNash equilibrium
dc.subjectevolutionarily stable strategies
dc.subjectevolutionary information search dynamics
dc.titleThe Value of Information Searching against Fake Newseng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleModelling, dynamics and games
oaire.awardURIhttp://hdl.handle.net/10400.8/13667
oaire.citation.endPage18
oaire.citation.issue12
oaire.citation.startPage1
oaire.citation.titleEntropy
oaire.citation.volume22
oaire.fundingStream3599-PPCDT
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameGouveia Martins
person.givenNameJosé Maria
person.identifier.orcid0000-0002-0556-7861
relation.isAuthorOfPublication29fc5be8-b5a2-489c-92d3-c0efe7e57892
relation.isAuthorOfPublication.latestForDiscovery29fc5be8-b5a2-489c-92d3-c0efe7e57892
relation.isProjectOfPublicationee48abd1-b5a3-46a2-8a2a-22915ea226ba
relation.isProjectOfPublication.latestForDiscoveryee48abd1-b5a3-46a2-8a2a-22915ea226ba

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Inspired by the Daley-Kendall and Goffman-Newill models, we propose an Ignorant-Believer-Unbeliever rumor (or fake news) spreading model with the following characteristics: (i) a network contact between individuals that determines the spread of rumors; (ii) the value (cost versus benefit) for individuals who search for truthful information (learning); (iii) an impact measure that assesses the risk of believing the rumor; (iv) an individual search strategy based on the probability that an individual searches for truthful information; (v) the population search strategy based on the proportion of individuals of the population who decide to search for truthful information; (vi) a payoff for the individuals that depends on the parameters of the model and the strategies of the individuals. Furthermore, we introduce evolutionary information search dynamics and study the dynamics of population search strategies. For each value of searching for information, we compute evolutionarily stable information (ESI) search strategies (occurring in non-cooperative environments), which are the attractors of the information search dynamics, and the optimal information (OI) search strategy (occurring in (eventually forced) cooperative environments) that maximizes the expected information payoff for the population. For rumors that are advantageous or harmful to the population (positive or negative impact), we show the existence of distinct scenarios that depend on the value of searching for truthful information. We fully discuss which evolutionarily stable information (ESI) search strategies and which optimal information (OI) search strategies eradicate (or not) the rumor and the corresponding expected payoffs. As a corollary of our results, a recommendation for legislators and policymakers who aim to eradicate harmful rumors is to make the search for truthful information free or rewarding.
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