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Sentiment Relation Detection between Main Characters in Turkish Stories

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dc.contributor.authorGanbarli, Samir
dc.contributor.authorDiri, Banu
dc.date.accessioned2026-06-27T14:58:39Z
dc.date.issued2024
dc.description.abstractThe rapid advancements in Natural Language Processing have facilitated tasks such as understanding texts and extracting information from them. Identifying main characters in texts or stories and detecting emotional relationships between characters is one of the current topics in Natural Language Processing. In this study, an application has been developed to identify main characters in Turkish stories and predict the emotional relationship between them using named entity recognition, dependency parsing, and sentiment analysis models. The success rate in extracting the main characters is about 77 and the success rate in determining the emotional relationship between them is about 41.en
dc.description.urihttps://doi.org/10.1109/siu61531.2024.10600820
dc.identifier.doi10.1109/siu61531.2024.10600820
dc.identifier.isbn979-8-3503-8897-8; 979-8-3503-8896-1
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.14981/66668
dc.identifier.wos001297894700085
dc.language.isotur
dc.publisherIEEE
dc.relation.conference32nd IEEE Signal Processing and Communications Applications Conference (SIU)
dc.relation.ispartof32ND IEEE SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU 2024
dc.subjectCharacter identification
dc.subjectdependency parsing
dc.subjectRNN
dc.subjectLSTM
dc.subjectsentiment analysis
dc.subjectComputer Science
dc.subjectEngineering
dc.subjectTelecommunications
dc.titleSentiment Relation Detection between Main Characters in Turkish Stories
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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