A multilayer network analysis of hashtags in twitter via co-occurrence and semantic links

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dc.contributor.authorTurker, Ilker
dc.contributor.authorSulak, Eyub Ekmel
dc.date.accessioned2024-09-29T16:04:50Z
dc.date.available2024-09-29T16:04:50Z
dc.date.issued2018
dc.departmentKarabük Üniversitesien_US
dc.description.abstractComplex network studies, as an interdisciplinary framework, span a large variety of subjects including social media. In social networks, several mechanisms generate miscellaneous structures like friendship networks, mention networks, tag networks, etc. Focusing on tag networks (namely, hashtags in twitter), we made a two-layer analysis of tag networks from a massive dataset of Twitter entries. The first layer is constructed by converting the co-occurrences of these tags in a single entry (tweet) into links, while the second layer is constructed converting the semantic relations of the tags into links. We observed that the universal properties of the real networks like small-world property, clustering and power-law distributions in various network parameters are also evident in the multilayer network of hashtags. Moreover, we outlined that co-occurrences of hashtags in tweets are mostly coupled with semantic relations, whereas a small number of semantically unrelated, therefore random links reduce node separation and network diameter in the co-occurrence network layer. Together with the degree distributions, the power-law consistencies of degree difference, edge weight and cosine similarity distributions in both layers are also appealing forms of Zipf's law evident in nature.en_US
dc.identifier.doi10.1142/S0217979218500297
dc.identifier.issn0217-9792
dc.identifier.issn1793-6578
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85029724805en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1142/S0217979218500297
dc.identifier.urihttps://hdl.handle.net/20.500.14619/6332
dc.identifier.volume32en_US
dc.identifier.wosWOS:000423843400001en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWorld Scientific Publ Co Pte Ltden_US
dc.relation.ispartofInternational Journal of Modern Physics Ben_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectComplex networksen_US
dc.subjectsocial networksen_US
dc.subjectsemantic networksen_US
dc.subjectdegree correlationsen_US
dc.subjectassortativityen_US
dc.subjectZipf's lawen_US
dc.titleA multilayer network analysis of hashtags in twitter via co-occurrence and semantic linksen_US
dc.typeArticleen_US

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