Classificationof Social Media Shares Using Sentiment Analysis

dc.contributor.authorBaykara, Muhammet
dc.contributor.authorGurturk, Ugur
dc.date.accessioned2026-08-12T16:41:15Z
dc.date.issued2017
dc.departmentFırat Üniversitesi
dc.description2017 International Conference on Computer Science and Engineering (UBMK) -- OCT 05-08, 2017 -- Antalya, TURKEY
dc.description.abstractThe use of social media is increasing rapidly today. With this increase, there is a lot of meaningful and meaningless data in social media environments. Parallel to this data formation, new working areas have also been formed. Sentiment analysis is an important area of study for generating meaningful information from this large data set. The sentiment analysis study, objectively indicates whether a phrase is positive, neutral or negative. That is, it is the process of determining whether the content is positive, negative or neutral. In this study, the analysis of the shares belonging to a certain Twitter user was performed by sentiment analysis method. Bayes algorithm is used in the analysis phase. Moreover, classification of users' categorization (news, politics, culture) according to their content has been successfully accomplished.
dc.description.sponsorshipIEEE Adv Technol Human,Istanbul Teknik Univ,Gazi Univ,Atilim Univ,TBV,Akdeniz Univ,Tmmob Bilgisayar Muhendisleri Odasi
dc.identifier.endpage916
dc.identifier.isbn978-1-5386-0930-9
dc.identifier.orcid0000-0001-5223-1343
dc.identifier.scopus2-s2.0-85040566847
dc.identifier.scopusqualityN/A
dc.identifier.startpage911
dc.identifier.urihttps://hdl.handle.net/11508/45753
dc.identifier.wosWOS:000426856900171
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIeee
dc.relation.ispartof2017 International Conference on Computer Science and Engineering (Ubmk)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260511
dc.subjectsentiment analysis
dc.subjectdata mining
dc.subjectbig data
dc.subjectsocial media analysis
dc.titleClassificationof Social Media Shares Using Sentiment Analysis
dc.title.alternativeSosyal Medya Paylaşimlarn n Duygu Analizi Yöntemiyle Sniflandirlmasi
dc.typeConference Object

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