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Automatic Detection of Influencers in Social Networks: Authority versus Domain signals

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dc.contributor.authorRodríguez Vidal, Javier
dc.contributor.authorAnaya Sánchez, Henry
dc.contributor.authorGonzalo Arroyo, Julio Antonio
dc.contributor.authorPlaza Morales, Laura
dc.date.accessioned2024-05-20T11:44:06Z
dc.date.available2024-05-20T11:44:06Z
dc.date.issued2019-01-07
dc.description.abstractGiven the task of finding influencers (opinion makers) for a given domain in a social network, we investigate (a) what is the relative importance of domain and authority signals, (b) what is the most effective way of combining signals (voting, classification, learning to rank, etc.) and how best to model the vocabulary signal, and (c) how large is the gap between supervised and unsupervised methods and what are the practical consequences. Our best results on the RepLab dataset (which improves the state of the art) uses language models to learn the domain-specific vocabulary used by influencers and combines domain and authority models using a Learning to Rank algorithm. Our experiments show that (a) both authority and domain evidence can be trained from the vocabulary of influencers; (b) once the language of influencers is modeled as a likelihood signal, further supervised learning and additional network-based signals only provide marginal improvements; and (c) the availability of training data sets is crucial to obtain competitive results in the task. Our most remarkable finding is that influencers do use a distinctive vocabulary, which is a more reliable signal than nontextual network indicators such as the number of followers, retweets, and so on.en
dc.description.versionversión final
dc.identifier.doihttps://doi.org/10.1002/asi.24156
dc.identifier.issn2330-1643, 2330-1635
dc.identifier.urihttps://hdl.handle.net/20.500.14468/12483
dc.journal.issue7
dc.journal.titleJournal of the Association for Information Science and Technology
dc.journal.volume70
dc.language.isoen
dc.publisherWiley
dc.relation.centerFacultades y escuelas::E.T.S. de Ingeniería Informática
dc.relation.departmentLenguajes y Sistemas Informáticos
dc.rightsAtribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subject.keywordsLearning to Rank
dc.subject.keywordsWeb and social media search
dc.subject.keywordsInformation extraction
dc.subject.keywordsSocial Network Analysis
dc.subject.keywordsNatural Language Processing
dc.subject.keywordsSocial Media Influencers
dc.titleAutomatic Detection of Influencers in Social Networks: Authority versus Domain signalses
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
person.familyNameGonzalo Arroyo
person.familyNamePlaza Morales
person.givenNameJulio Antonio
person.givenNameLaura
person.identifier.orcid0000-0002-5341-9337
person.identifier.orcid0000-0001-5144-8014
relation.isAuthorOfPublication0e0d6c85-2d8e-4fb3-9640-8ad17e875fcc
relation.isAuthorOfPublication29746aa9-9544-4364-8665-8b92a433fbfe
relation.isAuthorOfPublication.latestForDiscovery0e0d6c85-2d8e-4fb3-9640-8ad17e875fcc
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