Turkish Sentiment Analysis Using Machine Learning Methods: Application on Online Food Order Site Reviews
Abstract
Satisfaction measurement, which emerges in every sector today, is a very important factor for many companies. In this study, it is aimed to reach the highest accuracy rate with various machine learning algorithms by using the data on Yemek Sepeti and variations of this data. The accuracy values of each algorithm were calculated together with the various natural language processing methods used. While calculating these accuracy values, the parameters of the algorithms used were tried to be optimized. The models trained in this study on labeled data can be used on unlabeled data and can give companies an idea in measuring customer satisfaction. It was observed that 3 different natural language processing methods applied resulted in approximately 5% accuracy increase in most of the developed models.
Cite
@article{arxiv.2201.03848,
title = {Turkish Sentiment Analysis Using Machine Learning Methods: Application on Online Food Order Site Reviews},
author = {Özlem Aktaş and Berkay Coşkuner and İlker Soner},
journal= {arXiv preprint arXiv:2201.03848},
year = {2022}
}