Analyzing User Sentiments and Feedback Towards the Spotify App: A Sentiment Analysis of 51,000+ Reviews from Google Play Store

Abstract

This review investigates sentiment analysis methodologies applied to over 51,000 Google Play Store reviews of the Spotify mobile application. It synthesizes approaches ranging from lexicon-based models like VADER and TextBlob to machine learning and transformer-based architectures such as BERT and XLNet. Common positive and negative user feedback themes are identified and compared with analyses of competing apps including Netflix, YouTube, and Amazon Music. The review emphasizes the strengths and limitations of each method and outlines future directions for enhancing sentiment analysis pipelines in app review mining.