Hot topic detection and evaluation of multi-relation effects

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dc.contributor.authorZirbilek, Nadir Emre
dc.contributor.authorErakın, Mustafa
dc.contributor.authorÖzyer, Tansel
dc.contributor.authorAlhajj, Reda
dc.date.accessioned2022-02-28T10:33:54Z
dc.date.available2022-02-28T10:33:54Z
dc.date.issued2021
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractWith the growth of social media, Twitter has become one of the most popularly used microblogging communication platforms between people. Due to the wide preference of Twitter, popular issues in public, events like local or global news and daily life stories can immediately publish on Twitter. Thus, a substantial number of hot topics are created by Twitter users in real-time. These topics can exhibit every incident of everyday life. Therefore, detection of hot topics can be used in many applications such as observing public judgment, product recommendation, and incidence detection. In this paper, we propose a method for detecting Twitter hot topics and evaluate the effect of multi-relations such as retweets and hashtags on hot topics. The dataset was generated by fetching tweets for a certain time and location by using GetOldTweets3 API. Then using the LDA topic modeling algorithm the hot topics were identified for each multi relation. Finally, the effect of each relation is described by using the coherence scores)
dc.description.sponsorshipACM Special Interest Group on Knowledge Discovery in Data (SIGKDD) ; Elsevier ; IEEE Computer Society ; IEEE TCDE ; Springeren_US
dc.identifier.citationZirbilek, N. E., Erakın, M., Özyer, T. ve Alhajj, R. (2021). Hot topic detection and evaluation of multi-relation effects. 13th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM içinde (416-422. ss.). Virtual, Online, 8 November 2021. https://doi.org/10.1145/3487351.3490972
dc.identifier.doi10.1145/3487351.3490972
dc.identifier.endpage422
dc.identifier.isbn9781450391283
dc.identifier.scopus2-s2.0-85124380874
dc.identifier.scopusqualityN/A
dc.identifier.startpage416
dc.identifier.urihttps://doi.org/10.1145/3487351.3490972
dc.identifier.urihttps://hdl.handle.net/20.500.12511/9023
dc.indekslendigikaynakScopus
dc.institutionauthorÖzyer, Tansel
dc.language.isoen
dc.publisherAssociation for Computing Machinery, Inc
dc.relation.ispartof13th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAMen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectMulti-Relation Effects
dc.subjectEvaluation
dc.subjectHot Topic
dc.titleHot topic detection and evaluation of multi-relation effects
dc.typeConference Object

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