Türkçe Kozmetik Ürün Yorumlarının Duygu Analizi ile Değerlendirilmesi

Yıl 2025, Cilt: 7 Sayı: 2, 104 - 133, 31.12.2025

Cemile Gökçe Özmen , Selim Gündüz

https://doi.org/10.51541/nicel.1620960

Öz

Web temelli verilerin endüstriyi besleyen bir alan olması, bilgisayar bilimlerinin yanı sıra yönetim bilimlerinin araştırma konularına dahil olmasına neden olmuştur. İşletmelerin yeni ürünlerini piyasaya sürmesinde, yeniden şekillenmelerinde, stratejik kararlarında, pazarlama çalışmalarında yardımcı olan büyük veri, kurumların karar alma süreçlerinde oldukça etkilidir. Özellikle e-ticaret sitelerinde yer alan müşteri yorumları işletmeler ve markalar için kıymetli bilgileri içerisinde saklar. Denetimli makine öğrenme algoritmalarına istatiksel olarak dayanan duygu analizi, otomatik olarak bilgi çıkarımında fayda sağlayan önemli yöntemlerden biridir. Bu çalışmada, belirli bir kozmetik markasının trendyol.com e-ticaret sitesinde yer alan ürünlerine yönelik Türkçe müşteri değerlendirmeleri üzerinde duygu analizi gerçekleştirilmiştir. Veri seti pozitif, negatif ve nötr olarak sınıflandırılmış ve ardından K-En Yakın Komşular (K-NN), Destek Vektör Makinesi (SVM) ve Karar Ağacı (DT) algoritmaları kullanarak sınıflandırma performansları ölçülerek değerlendirilmiştir. Karşılaştırmalı analizler sonucunda her üç algoritma için değerlendirme metrikleri %85 oranının üzerinde sonuç vermiştir. Kullanılan algoritmalar içerisinde Destek Vektör Makinesi %91 doğruluk oranı ile en başarılı sonucu vermiştir.

Anahtar Kelimeler

Duygu Analizi , Makine Öğrenmesi , Doğal Dil İşleme , Python , Metin Madenciliği

Evaluation of Turkish cosmetic product reviews with machine learning-based sentiment analysis

Öz

Since web-based data is an area that feeds the industry, it has been included in the research topics of management sciences as well as computer sciences. Big data, which helps businesses launch new products and reshape strategic decisions and marketing studies, is very effective in the decisions-making processes in organizations. Customer reviews, especially on e-commerce sites, contain valuable information for businesses and brands. Sentiment analysis, which is statistically based on supervised machine learning algorithms, is one of the important methods that provide benefits in automatic information extraction. In this study, sentiment analysis was performed on Turkish costumer reviews about the cosmetic brand on trendyol.com e-commerce site. The dataset was classified as positive, negative, and neutral, and the classification performances were measured using K-Nearest Neighbours (K-NN), Support Vector Machine (SVM), and Decision Tree (DT) algorithms. As a result of comparative analysis, the evaluation metrics for all three algorithms yielded results above 85%. Support Vector Machine gave the most successful result with a 91% accuracy rate among the algorithms used.

Anahtar Kelimeler

Sentiment Analysis , Machine Learning , Natural Language Processing , Python , Text Mining

Kaynakça

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