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What’s in a Name?: How Perceived Music Playlist Personalization Influences Content Expectations
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.ORCID iD: 0000-0003-4344-9986
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics.
2023 (English)In: Human-Computer Interaction – INTERACT 2023: 19th IFIP TC13 International Conference, York, UK, August 28 – September 1, 2023, Proceedings, Part IV / [ed] J. A. Nocera, M. K. Lárusdóttir, H. Petrie, A. Piccinno, M. Winckler, Springer, 2023, Vol. 14145, p. 585-589Conference paper, Published paper (Refereed)
Abstract [en]

With the vast amount of online content available to us, platforms are utilizing recommender systems to help their users in their decision making. By presenting content that is in line with the user’s taste and preferences a personalized experience can be created. Platforms such as Netflix and Spotify have started to create an additional layer of personalization by framing of the content presentation through tailoring album art and titles towards the user. Even though all content in a user account is personalized, this additional layer of personalization creates a distinction between “regular" content and implied personalized content. In this work we explore how the textual framing (generic vs. personalized) of music playlists influences behaviors and content expectations. Our findings show that users mostly ignore the implied personalized playlists as they expect that it only consists of previously listened songs, while generic playlists are exploited to find new music to listen to.

Place, publisher, year, edition, pages
Springer, 2023. Vol. 14145, p. 585-589
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 14145
Keywords [en]
Content Expectations, Personalization, Recommendations, Decision making, Online systems, Content expectation, Content presentation, Decisions makings, Netflix, Online content, Personalizations, Personalized content, Recommendation, Music
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:hj:diva-62678DOI: 10.1007/978-3-031-42293-5_77Scopus ID: 2-s2.0-85173032802ISBN: 978-3-031-42292-8 (print)ISBN: 978-3-031-42293-5 (electronic)OAI: oai:DiVA.org:hj-62678DiVA, id: diva2:1805576
Conference
19th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2023 York 28 August 2023 through 1 September 2023
Available from: 2023-10-17 Created: 2023-10-17 Last updated: 2023-10-17Bibliographically approved

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Ferwerda, Bruce

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