Opinion dynamics via search engines (and other algorithmic gatekeepers)

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• dc.contributor.author Germano, Fabrizio
• dc.contributor.author Sobbrio, Francesco
• dc.date.accessioned 2025-01-27T12:55:04Z
• dc.date.available 2025-01-27T12:55:04Z
• dc.date.issued 2020
• dc.description Includes supplementary materials for the online appendix.
• dc.description.abstract Ranking algorithms are the information gatekeepers of the Internet era. We develop a stylized model to study the interplay between a ranking algorithm and individual clicking behavior. We consider a search engine that uses an algorithm based on popularity and on personalization. The analysis shows the presence of a feedback effect, whereby individuals clicking on websites indirectly provide information about their private signals to successive searchers through the popularity-ranking algorithm. Accordingly, when individuals provide sufficiently positive feedback to the ranking algorithm, popularity-based rankings tend to aggregate information while personalization acts in the opposite direction. Moreover, we find that, under fairly general conditions, popularity-based rankings generate an advantage of the fewer effect: fewer websites reporting a given signal attract relatively more traffic overall. This highlights a novel, ranking-driven channel that can potentially explain the diffusion of misinformation, as websites reporting incorrect information may attract an amplified amount of traffic precisely because they are few.
• dc.description.sponsorship Germano acknowledges financial support from grant ECO2017-89240-P (AEI/FEDER, UE), from Fundación BBVA (grant “Innovación e Información en la Economía Digital”) and also from the Spanish Ministry of Economy and Competitiveness, through the Severo Ochoa Programme for Centres of Excellence in R&D (SEV-2015-0563).
• dc.format.mimetype application/pdf
• dc.identifier.citation Germano F, Sobbrio F. Opinion dynamics via search engines (and other algorithmic gatekeepers). J Public Econ. 2020 Jul;187:104188. DOI: 10.1016/j.jpubeco.2020.104188
• dc.identifier.doi http://dx.doi.org/10.1016/j.jpubeco.2020.104188
• dc.identifier.issn 0047-2727
• dc.identifier.uri http://hdl.handle.net/10230/69297
• dc.language.iso eng
• dc.publisher Elsevier
• dc.relation.ispartof Journal of Public Economics. 2020 Jul;187:104188
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/SEV-2015-0563
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/ECO2017-89240-P
• dc.rights © Elsevier http://dx.doi.org/10.1016/j.jpubeco.2020.104188.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Ranking algorithm
• dc.subject.keyword Information aggregation
• dc.subject.keyword Asymptotic learning
• dc.subject.keyword Popularity ranking
• dc.subject.keyword Personalized ranking
• dc.subject.keyword Misinformation
• dc.subject.keyword Fake news
• dc.title Opinion dynamics via search engines (and other algorithmic gatekeepers)
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/acceptedVersion