Data Driven Positioning Analysis of Music Streaming Platforms

Ayse Basak Incekas; Umut Asan

doi:10.1007/978-3-031-39777-6_74

Data Driven Positioning Analysis of Music Streaming Platforms

Ayse Basak Incekas^*, Umut Asan

^*Corresponding author for this work

Department of Industrial Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Editors	Cengiz Kahraman, Irem Ucal Sari, Basar Oztaysi, Sezi Cevik Onar, Selcuk Cebi, A. Çağrı Tolga
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	634-641
Number of pages	8
ISBN (Print)	9783031397769
DOIs	https://doi.org/10.1007/978-3-031-39777-6_74
Publication status	Published - 2023
Event	Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference - Istanbul, Turkey Duration: 22 Aug 2023 → 24 Aug 2023

Publication series

Name	Lecture Notes in Networks and Systems
Volume	759 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Country/Territory	Turkey
City	Istanbul
Period	22/08/23 → 24/08/23

Bibliographical note

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

Keywords

BERTopic
Customer reviews
Music streaming platforms
Sentiment analysis

Access to Document

10.1007/978-3-031-39777-6_74

Cite this

Incekas, A. B., & Asan, U. (2023). Data Driven Positioning Analysis of Music Streaming Platforms. In C. Kahraman, I. U. Sari, B. Oztaysi, S. Cevik Onar, S. Cebi, & A. Ç. Tolga (Eds.), Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference (pp. 634-641). (Lecture Notes in Networks and Systems; Vol. 759 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-39777-6_74

Incekas, Ayse Basak ; Asan, Umut. / Data Driven Positioning Analysis of Music Streaming Platforms. Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. editor / Cengiz Kahraman ; Irem Ucal Sari ; Basar Oztaysi ; Sezi Cevik Onar ; Selcuk Cebi ; A. Çağrı Tolga. Springer Science and Business Media Deutschland GmbH, 2023. pp. 634-641 (Lecture Notes in Networks and Systems).

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title = "Data Driven Positioning Analysis of Music Streaming Platforms",

abstract = "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.",

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Incekas, AB & Asan, U 2023, Data Driven Positioning Analysis of Music Streaming Platforms. in C Kahraman, IU Sari, B Oztaysi, S Cevik Onar, S Cebi & AÇ Tolga (eds), Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. Lecture Notes in Networks and Systems, vol. 759 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 634-641, Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference, Istanbul, Turkey, 22/08/23. https://doi.org/10.1007/978-3-031-39777-6_74

Data Driven Positioning Analysis of Music Streaming Platforms. / Incekas, Ayse Basak; Asan, Umut.
Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. ed. / Cengiz Kahraman; Irem Ucal Sari; Basar Oztaysi; Sezi Cevik Onar; Selcuk Cebi; A. Çağrı Tolga. Springer Science and Business Media Deutschland GmbH, 2023. p. 634-641 (Lecture Notes in Networks and Systems; Vol. 759 LNNS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Incekas, Ayse Basak

AU - Asan, Umut

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

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KW - Music streaming platforms

KW - Sentiment analysis

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PB - Springer Science and Business Media Deutschland GmbH

T2 - Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference

Y2 - 22 August 2023 through 24 August 2023

ER -

Incekas AB, Asan U. Data Driven Positioning Analysis of Music Streaming Platforms. In Kahraman C, Sari IU, Oztaysi B, Cevik Onar S, Cebi S, Tolga AÇ, editors, Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference. Springer Science and Business Media Deutschland GmbH. 2023. p. 634-641. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-031-39777-6_74