Εμφάνιση απλής εγγραφής

dc.creatorRazis G., Anagnostopoulos I., Zeadally S.en
dc.date.accessioned2023-01-31T09:51:19Z
dc.date.available2023-01-31T09:51:19Z
dc.date.issued2020
dc.identifier10.1145/3369780
dc.identifier.issn03600300
dc.identifier.urihttp://hdl.handle.net/11615/78480
dc.description.abstractThe discovery of influential entities in all kinds of networks (e.g., social, digital, or computer) has always been an important field of study. In recent years, Online Social Networks (OSNs) have been established as a basic means of communication and often influencers and opinion makers promote politics, events, brands, or products through viral content. In this work, we present a systematic review across (i) online social influence metrics, properties, and applications and (ii) the role of semantic in modeling OSNs information. We found that both areas can jointly provide useful insights towards the qualitative assessment of viral user-generated content, as well as for modeling the dynamic properties of influential content and its flow dynamics. © 2020 Association for Computing Machinery.en
dc.language.isoenen
dc.sourceACM Computing Surveysen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85079572549&doi=10.1145%2f3369780&partnerID=40&md5=9df232b10e221eac566cd471cbb59034
dc.subjectSemantic Weben
dc.subjectSemanticsen
dc.subjectSocial networking (online)en
dc.subjectDynamic propertyen
dc.subjectInformation qualityen
dc.subjectOnline social networks (OSNs)en
dc.subjectQualitative assessmentsen
dc.subjectSocial influenceen
dc.subjectSocial semanticsen
dc.subjectSystematic Reviewen
dc.subjectUser-generated contenten
dc.subjectEconomic and social effectsen
dc.subjectAssociation for Computing Machineryen
dc.titleModeling influence with semantics in social networks: A surveyen
dc.typeotheren


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Εμφάνιση απλής εγγραφής