Show simple item record

dc.creatorJain, Somya
dc.creatorSinha, Adwitiya
dc.date.accessioned2020-08-21T15:44:35Z
dc.date.available2020-08-21T15:44:35Z
dc.date.created2020
dc.identifier.issn0960-0779spa
dc.identifier.otherhttps://doi.org/10.1016/j.chaos.2020.110037spa
dc.identifier.urihttp://hdl.handle.net/20.500.12010/12086
dc.description.abstractIn the era of advanced mobile technology, freedom of expression over social media has become prevalent among online users. This generates a huge amount of communication that eventually forms a ground for extensive research and analysis. The social network analysis allows identifying the influential people in society over microblogging platforms. Twitter, being an evolving social media platform, has become increasingly vital for online dialogues, trends, and content virality. Applications of discovering influential users over Twitter are manifold. It includes viral marketing, brand analysis, news dissemination, health awareness spreading, propagating political movement, and opinion leaders for empowering governance. In our research, we have proposed a sustainable approach, namely Weighted Correlated Influence (WCI), which incorporates the relative impact of timeline-based and trend-specific features of online users. Our methodology considers merging the profile activity and underlying network topology to designate online users with an influence score, which represents the combined effect. To quantify the performance of our proposed method, the Twitter trend #CoronavirusPandemic is used. Also, the results are validated for another social media trend. The experimental outcomes depict enhanced performance of proposed WCI over existing methods that are based on precision, recall, and F1-measure for validation.spa
dc.format.extent8 páginasspa
dc.format.mimetypeimage/jepgspa
dc.language.isoengspa
dc.publisherChaos, Solitons and Fractalsspa
dc.sourcereponame:Expeditio Repositorio Institucional UJTLspa
dc.sourceinstname:Universidad de Bogotá Jorge Tadeo Lozanospa
dc.subjectSocial Networkspa
dc.subjectInfluence measurespa
dc.subjectWeighted Correlated Influencespa
dc.subjectSustainable Computingspa
dc.subjectTwitterspa
dc.subjectCovid-19spa
dc.titleIdentification of influential users on Twitter: A novel weighted correlated influence measure for Covid-19spa
dc.type.localArtículospa
dc.subject.lembSíndrome respiratorio agudo gravespa
dc.subject.lembCOVID-19spa
dc.subject.lembSARS-CoV-2spa
dc.subject.lembCoronavirusspa
dc.rights.accessrightsinfo:eu-repo/semantics/embargoedAccessspa
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersionspa
dc.rights.localAcceso restringidospa
dc.identifier.doihttps://doi.org/10.1016/j.chaos.2020.110037spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record