SENTIMENT ANALYSIS OF COMMENTS IN UZBEK LANGUAGE

Sentiment analysis of many comments written by users and extracting useful information for solving classification problems is an important task of natural language processing (NLP). This can affect not only customer satisfaction, but also the further development of the company. In this article, we have prepared a Dataset using feedback given to restaurants located in the city of Tashkent on the Google map and analyzed Sentiment using Logistic Regression models. Overall evaluation results show that the system performs well by performing pre-processing steps such as stemming for agglutinative languages, resulting in 91% accuracy in the best performing model.