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Words, Meanings, Characters in Sentiment Analysis

dc.contributor.authorAmasyali, Mehmet Fatih
dc.contributor.authorTaskopru, Hakan
dc.contributor.authorCaliskan, Kubra
dc.date.accessioned2026-06-27T14:20:35Z
dc.date.issued2018
dc.description.abstractIn the sentiment analysis, text representation is the most important research topic as another natural language processing tasks. In this study, word, semantic and character based representations of texts are compared for Turkish sentiment analysis. Classical and deep learning based approaches are used in data modeling. Character-based representations are more successful with both classical and deep learning based approaches. Moreover, a large-scale tagged data set has been presented for Turkish sentiment analysis researchers.en
dc.identifier.endpage14
dc.identifier.isbn978-1-5386-7786-5
dc.identifier.startpage9
dc.identifier.urihttps://hdl.handle.net/20.500.14981/59481
dc.identifier.wos000455592800034
dc.language.isotur
dc.publisherIEEE
dc.relation.conferenceInnovations in Intelligent Systems and Applications Conference (ASYU)
dc.relation.ispartof2018 INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS CONFERENCE (ASYU)
dc.subjectsentiment analysis
dc.subjectnatural language processing
dc.subjectbag of words
dc.subjectword2vec
dc.subjectfasttext
dc.subjectconvolutionanl neural networks
dc.subjectlong short term memory networks
dc.subjectComputer Science
dc.subjectEngineering
dc.titleWords, Meanings, Characters in Sentiment Analysis
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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