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Framing theory on music streaming platforms: How vocabulary influences the user experience
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
2023 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Music streaming services aim to provide users with personalized content to avoid information overload and increase the user experience. Besides the recommender systems that are involved to ensure users are provided with their musical preferences, vocabulary can play a significant role in achieving personalization. Including personal pronouns is one way to implement personalization. However, looking into music streaming services it has yet to be discovered how the implementation of personalization via wording has its effect on the users' decisions, expectations, and satisfaction.

The study aims to get a better understanding of how vocabulary framing in personalized playlist titles affects the user experience. The lack of knowledge makes it difficult to make wise decisions in wording and it could lead to ineffective use of vocabulary within playlist titles on music streaming services. 

To carry out this study an online survey was conducted, and the data collected was stored in an API spreadsheet. The program SPSS was then used to further analyse the data to draw conclusions. Based on the results of the survey it was concluded that using wording that indicates personalization does have a significant effect on user choice and overall satisfaction within a music streaming platform. When given the choice of picking either a playlist with a title that indicates personalization or one where there is no indication of personalization, participants were significantly more drawn towards the playlists that indicate personalization. 

Place, publisher, year, edition, pages
2023. , p. 54
Keywords [en]
Framing Theory, Wording Effect, User Experience, Personalization, Satisfaction, Expectations
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:hj:diva-61858ISRN: JU-JTH-IKA-2-20230306OAI: oai:DiVA.org:hj-61858DiVA, id: diva2:1779401
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Available from: 2023-07-06 Created: 2023-07-04 Last updated: 2025-10-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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