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dc.contributor.authorShoeibi, Niloufar
dc.contributor.authorMartín Mateos, Alberto
dc.contributor.authorRivas Camacho, Alberto 
dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.contributor.authorMartin Mateos, Alberto
dc.date.accessioned2022-05-27T10:59:14Z
dc.date.available2022-05-27T10:59:14Z
dc.date.issued2022
dc.identifier.citationShoeibi, N., et al. (2022). A Feature Based Approach on Behavior Analysis of the Users on Twitter: A Case Study of AusOpen Tennis Championship. Advances in Intelligent Systems and Computing, vol 1237. Springer, Cham.es_ES
dc.identifier.isbn978-3-030-53035-8
dc.identifier.urihttp://hdl.handle.net/10366/149872
dc.description.abstract[EN] Due to the advancement of technology, and the promotion of smart- phones, using social media got more and more popular. Nowadays, it has become an undeniable part of people’s lives. So, they will create a flow of information by the content they share every single moment. Analyzing this information helps us to have a better understanding of users, their needs, their tendencies and classify them into different groups based on their behavior. These behaviors are various and due to some extracted features, it is possible to categorize the users into different categories. In this paper, we are going to focus on Twitter users and the AusOpen Tennis championship event as a case study. We define the attributions describing each class and then extract data and identify features that are more correlated to each type of user and then label user type based on the reasoning model. The results contain 4 groups of users; Verified accounts, Influencers, Regular profiles, and Fake profiles.es_ES
dc.language.isoenges_ES
dc.publisherSpringerLinkes_ES
dc.relation.ispartofseriesAISC;1237
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSocial media analyticses_ES
dc.subjectBehavior analysises_ES
dc.subjectUser behavior mininges_ES
dc.subjectFeature extractiones_ES
dc.subjectTwitteres_ES
dc.subjectVerifiedes_ES
dc.subjectInfluencerses_ES
dc.subjectRegular and fakeses_ES
dc.titleA feature based approach on behavior analysis of the users on twitter: A case study of AusOpen tennis championshipes_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.relation.publishversionhttps://link.springer.com/chapter/10.1007/978-3-030-53036-5_31
dc.identifier.doi10.1007/978-3-030-53036-5_31
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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