Tripadvisor Kullanıcılarının Türkçe ve İngilizce Yorumları Kapsamında Duygu Analizi Yöntemlerinin Karşılaştırmalı Analizi.
The aim of the research is to compare the sentiment analysis methods used to reveal and classify the emotional tendencies in Turkish and English comments of hotel users. Within purpose, classification algorithms such as Decision Tree and Random Forest from machine learning methods were used. The dat...
| Publicado en: | Journal of Abant Social Sciences / Abant Sosyal Bilimler Dergisi Vol. 22; no. 2; pp. 901 - 917 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Journal of Abant Social Sciences
jul2022
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=175288655&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 175288655 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 27579425 N14N jtl: Journal of Abant Social Sciences / Abant Sosyal Bilimler Dergisi issn: 27579425 maglogo: N pubinfo: dt: jul2022 vid: 22 iid: 2 pid: 81378 pub: Journal of Abant Social Sciences artinfo: ui: 175288655 10.11616/asbi.1103992 ppf: 901 ppct: 16 formats: tig: atl: Tripadvisor Kullanıcılarının Türkçe ve İngilizce Yorumları Kapsamında Duygu Analizi Yöntemlerinin Karşılaştırmalı Analizi. aug: au: Polat, Hıdır Ağca, Yılmaz affil: Tokat Gaziosmanpaşa Üniversitesi. su: Emotions Text mining sug: subj: Emotions Text mining keyword: data mining emotion analysis text mining User reviews duygu analizi Kullanıcı yorumları metin madenciliği TripAdvisor veri madenciliği data mining emotion analysis text mining User reviews duygu analizi Kullanıcı yorumları metin madenciliği TripAdvisor veri madenciliği ab: The aim of the research is to compare the sentiment analysis methods used to reveal and classify the emotional tendencies in Turkish and English comments of hotel users. Within purpose, classification algorithms such as Decision Tree and Random Forest from machine learning methods were used. The data was obtained from Tripadvisor tourism portal with web scraping/mining technique within the scope of this study, which shows quantitative research feature. A purposeful sampling method was used in this study. Emotion analysis, which is one of the text mining applications, was used to analyze the data. KNIME Analytics Platform was used in the data analysis process. As a result of the research, it was seen that the machine learning algorithms performed more effective classification than dictionary-based analysis. In addition, the machine learning algorithms produced more successful results in the Turkish language comments at the classification stage. pubtype: Academic Journal doctype: Article src: R language: Turkish refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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