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Virality, only the tip of the iceberg: ways of spread and interaction around COVID-19 misinformation in Twitter

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Human Language and Accessibility Technologies (HULAT)es
dc.contributor.authorVillar Rodriguez, Guillermo
dc.contributor.authorSouto Rico, Monica Maria
dc.contributor.authorMartín, Alejandro
dc.contributor.authorVillar Rodríguez, Guillermo
dc.contributor.authorSouto Rico, Mónica María
dc.contributor.authorMartín, Alejandro
dc.contributor.funderComunidad de Madriden
dc.contributor.funderEuropean Commissiones
dc.contributor.funderMinisterio de Ciencia e Innovación (España)es
dc.date.accessioned2023-12-13T08:48:10Z
dc.date.available2023-12-13T08:48:10Z
dc.date.issued2022-04-01
dc.description.abstractMisinformation has long been a weapon that helps the political, social, and economic interests of different sectors. This became more evident with the transmission of false information in the COVID-19 pandemic, compromising citizens' health by anti-vaccine recommendations, the denial of the coronavirus and false remedies. Online social networks are the breeding ground for falsehoods and conspiracy theories. Users can share viral misinformation or publish it on their own. This encourages a double analysis of this issue: the need to capture the deluge of false information as opposed to the real one and the study of users' patterns to interact with that infodemic. As a response to this, our work combines the use of artificial intelligence and journalism through fact-checked false claims to provide an in-depth study of the number of retweets, likes, replies, quotes and repeated texts in posts stating or contradicting misinformation in Twitter. The large sample of tweets was collected and automatically analysed through Natural Language Processing (NLP) techniques, not to give all the attention only to the posts with a big impact but to all the messages contributing to the expansion of false information or its rejection regardless of their virality. This analysis revealed that the diffusion of tweets surrounding coronavirus-related misinformation is not only a domain of viral tweets, but also from posts without interactions, which represent most of the sample, and that there are no big differences between misinformation and its contradiction in general, except for the use of replies.en
dc.description.sponsorshipThis work has been supported by the research project CIVIC: “Intelligent characterisation of the veracity of the information related to COVID-19”, granted by BBVA Foundation Grants for Scientific Research Groups SARS CoV-2 and COVID-19, by the Spanish Ministry of Science and Innovation under FightDIS (PID2020-117263GB-100) and XAI-Disinfodemics (PLEC2021-007681) grants, by Comunidad Autónoma de Madrid under S2018/TCS-4566 grant, by European Commission under IBERIFIER - Iberian Digital Media Research and Fact-Checking Hub (2020-EU-IA-0252), by “Convenio Plurianual with the Universidad Politécnica de Madrid in the actuation line of Programa de Excelencia para el Profesorado Universitario” and by the research project DisTrack: “Tracking disinformation in Online Social Networks through Deep Natural Language Processing”, granted by Barcelona Mobile World Capital Foundationen
dc.identifier.bibliographicCitationVillar-Rodríguez, G., Souto-Rico, M., & Martín, A. (2022). Virality, only the tip of the iceberg: ways of spread and interaction around COVID-19 misinformation in Twitter. Communication & Society, 35(2), 239-256. https://doi.org/10.15581/003.35.2.239-256en
dc.identifier.doihttp://dx.doi.org/10.15581/003.35.2.239-256
dc.identifier.issn2386-7876
dc.identifier.publicationfirstpage239
dc.identifier.publicationissue2
dc.identifier.publicationlastpage256
dc.identifier.publicationtitleCommunication and Societyen
dc.identifier.publicationvolume35
dc.identifier.urihttps://hdl.handle.net/10016/39078
dc.identifier.uxxiAR/0000032735
dc.language.isoeng
dc.publisherUniversidad de Navarraes
dc.relation.projectIDComunidad de Madrid. S2018/TCS-4566es
dc.relation.projectIDinfo:eu-repo/2020-EU-IA-0252
dc.rights© 2022 Communication & Societyen
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaCiencias de la Informaciónes
dc.subject.ecienciaMedicinaes
dc.subject.ecienciaSociologíaes
dc.subject.othermisinformationen
dc.subject.otherartificial intelligenceen
dc.subject.othertwitteren
dc.subject.othercovid-19en
dc.subject.othernatural language processing (NLP)en
dc.titleVirality, only the tip of the iceberg: ways of spread and interaction around COVID-19 misinformation in Twitteren
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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