Data Driven Positioning Analysis of Music Streaming Platforms

Incekas A. B., Asan U.

Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference, İstanbul, Turkey, 22 - 24 August 2023, vol.759 LNNS, pp.634-641 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 759 LNNS
  • Doi Number: 10.1007/978-3-031-39777-6_74
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.634-641
  • Keywords: BERTopic, Customer reviews, Music streaming platforms, Sentiment analysis
  • Istanbul Technical University Affiliated: Yes


This study investigates the market position of music streaming platforms by analyzing user sentiment and topics expressed in customer reviews. In contrast to traditional methods, this study employs machine learning techniques to extract less biased and more authentic comments from user review data. Sentiment and topic analysis are utilized to identify the emotional tone of the language used and distinct topics discussed within customer reviews of the four most popular music streaming platforms, namely Spotify, Amazon Music, Apple Music, and YouTube Music. The study comprises four main steps, including data collection, cleaning and pre-processing, sentiment analysis, and topic modeling. The results reveal that Amazon Music is prominent in functionality aspects, while Spotify ranks highest across all topics. Apple and YouTube Music have the highest scores in reviews related to customization. The proposed approach provides valuable insights into user perceptions and preferences, which can assist brands in improving their market position. The paper concludes with a summary of the findings, marketing implications, and suggestions for future research.