TRIPADVISOR KULLANICILARININ TÜRKÇE VE İNGİLİZCE YORUMLARI KAPSAMINDA DUYGU ANALİZİ YÖNTEMLERİNİN KARŞILAŞTIRMALI ANALİZİ

Yıl 2022, , 901 - 916, 31.07.2022

Hıdır Polat , Yılmaz Ağca

https://doi.org/10.11616/asbi.1103992

Cited By: 5

Öz

Araştırmanın amacı, TripAdvisor kullanıcılarının Türkçe ve İngilizce yorumlarındaki duygusal eğilimlerin ortaya çıkarılması ve sınıflandırılmasında kullanılan duygu analizi yöntemlerini karşılaştırmaktır. Amaç kapsamında makine öğrenme yöntemlerinden Decision Tree, Random Forest gibi sınıflandırma algoritmaları kullanılmıştır. Nicel araştırma özelliği gösteren bu çalışma kapsamında veriler, TripAdvisor turizm portalından web kazıma tekniği ile elde edilmiştir. Amaçsal örnekleme yönteminin benimsendiği bu çalışmada verilerin analiz edilmesi sürecinde duygu analizi yöntemi kullanılmıştır. Veri analiz sürecinde açık kaynak kodlu KNİME veri madenciliği programından yararlanılmıştır. Araştırma neticesinde makine öğrenme algortimalarının sözlük tabanlı analize göre daha etkin sınıflandırma gerçekleştirdiği görülmüştür. Ayrıca makine öğrenme algortimaları sınıflandırma aşamasında Türkçe dilindeki yorumlarda daha başarılı sonuçlar üretmiştir.

Anahtar Kelimeler

Kullanıcı yorumları, veri madenciliği, metin madenciliği, duygu analizi, TripAdvisor

Destekleyen Kurum

Yok

Proje Numarası

Yok

COMPARATIVE ANALYSIS OF EMOTION ANALYSIS METHODS WITHIN THE SCOPE OF HOTEL USERS TURKISH AND ENGLISH COMMENTS

Öz

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.

Anahtar Kelimeler

User reviews, data mining, text mining, emotion analysis, TripAdvisor

Proje Numarası

Yok

Kaynakça

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