The Impact of Artificial Intelligence on Sentiment Analysis Detection in Music Reviews

Year 2025, Volume: 13 Issue: 3, 243 - 252, 30.09.2025

Murat Şimşek , Buğra Kağan Kayhan

https://doi.org/10.17694/bajece.1492287

Abstract

This study aims to perform sentiment and content analysis of Spotify user reviews using machine learning and deep learning methods. The goal is to better understand users' experiences and satisfaction. The study employs various machine learning and deep learning techniques to identify the emotional tendencies in user reviews and analyze the relationship between these tendencies and content features. The performance of these methods is evaluated using various metrics such as accuracy, precision, recall, and F1-score. By identifying the strengths and weaknesses of each method, the study determines which techniques are more effective in specific situations. The results provide valuable insights for improving the quality of music streaming services and enhancing user experience. This study aims to help service providers increase user satisfaction by gaining a better understanding of user feedback. Additionally, these analyses are expected to provide valuable data for future improvements in music streaming services. Thus, it will be possible to continuously improve user experiences and enhance service quality.

Keywords

Sentiment Analysis , Machine Learning , Deep Learning , Large Language Model , Natural Language Processing , LSTM

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