Data Driven Positioning Analysis of Music Streaming Platforms

Ayse Basak Incekas*, Umut Asan

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

Özet

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.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
EditörlerCengiz Kahraman, Irem Ucal Sari, Basar Oztaysi, Sezi Cevik Onar, Selcuk Cebi, A. Çağrı Tolga
YayınlayanSpringer Science and Business Media Deutschland GmbH
Sayfalar634-641
Sayfa sayısı8
ISBN (Basılı)9783031397769
DOI'lar
Yayın durumuYayınlandı - 2023
EtkinlikIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference - Istanbul, Turkey
Süre: 22 Ağu 202324 Ağu 2023

Yayın serisi

AdıLecture Notes in Networks and Systems
Hacim759 LNNS
ISSN (Basılı)2367-3370
ISSN (Elektronik)2367-3389

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???event.eventtypes.event.conference???Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot22/08/2324/08/23

Bibliyografik not

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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