Relevant bibliographies by topics / Playlists

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Playlists'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Playlists"

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Law, Man Hei, and Andrew B. Horner. "Emotion equalization app: The effectiveness of dynamic music therapy approaches." Journal of the Acoustical Society of America 155, no. 3_Supplement (2024): A193—A194. http://dx.doi.org/10.1121/10.0027274.

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A recent study explored how static music playlists of relaxing or uplifting music can improve our mood. Unlike static playlists that rely exclusively on relaxing, uplifting, or consoling music, this study explores eight distinct methods to curate playlists. These approaches include transitions from one dimension to another (e.g., Angry-to-Relaxing, Angry-Uplifting, Relaxing-Uplifting, Relaxing- Natural, Sad-Relaxing, Sad-Uplifting, Uplifting-Relaxing, and Uplifting-Natural). To evaluate the effectiveness of these playlists, online experiments were conducted, wherein participants were surveyed
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Dhaenens, Frederik, and Jean Burgess. "‘Press play for pride’: The cultural logics of LGBTQ-themed playlists on Spotify." New Media & Society 21, no. 6 (2018): 1192–211. http://dx.doi.org/10.1177/1461444818808094.

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This article explores the cultural practice of creating lesbian, gay, bisexual, transgender, and queer (LGBTQ)-themed playlists on music streaming services. It aims to understand how LGBTQ identities and cultures are represented and negotiated through the use of, and shaped by, digital media platforms. Through the textual analysis of 37 LGBTQ-themed Spotify playlists, we identified four cultural logics that structure the practice of playlist curation, each of which demonstrates the significance of music consumption to individual identity work and collective belonging. We conclude that the prac
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Pichl, Martin, Eva Zangerle, and Günther Specht. "Understanding User-Curated Playlists on Spotify." International Journal of Multimedia Data Engineering and Management 8, no. 4 (2017): 44–59. http://dx.doi.org/10.4018/ijmdem.2017100103.

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Music streaming platforms enable people to access millions of tracks using computers and mobile devices. However, users cannot browse manually millions of tracks to find music they like. Building recommender systems suggesting music fitting the current context of a user is a challenging task. A deeper understanding for the characteristics of user-curated playlists naturally contributes to more personalized recommendations. To get a deeper understanding of how users organize music nowadays, we analyze user-curated playlists from the music streaming platform Spotify. Based on the audio features
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Ahnaf, Fikra. "From listening to curating: Anthropological curatorship toward music playlist practices." ETNOSIA : Jurnal Etnografi Indonesia 8, no. 2 (2023): 271–89. http://dx.doi.org/10.31947/etnosia.v8i2.30162.

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Currently, the curatorial approach is expanding its influence beyond the limitations of museums and art galleries, transforming the experiences and significance of our daily existence. That is embodied, for example, in the curatorial practices of music playlists. In making a music playlist there must be a sound curation process where the songs to listen to are selected and included in the music playlist. Accordingly, this study aims to describe how users of analog (mixtapes) and digital (Spotify playlist) music playlists conduct their music curation process and perceive the relationships behin
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Vargas, Emiliano. "Socio-semiotic considerations about playlists." Punctum. International Journal of Semiotics 09, no. 01 (2023): 189–204. http://dx.doi.org/10.18680/hss.2023.0011.

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This paper analyzes the notion of playlists as a socio-semiotic category in the context of the mediatization of contemporary popular music by studying its uses in virtual and non-virtual communities. We propose that the digital mediatization of playlists affects contemporary cultural forms, shaping social modes of conceiving music as they enable new forms of interaction in the present moment. Our investigation focuses on different ways digital mediatization of playlists contributes to creating virtual communities and transforming performative practices in non-virtual communities of musicians.
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Yadav, Ram Ashish. "Dynamic Playlist Generation using Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem32579.

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This study investigates the application of machine learning algorithms for dynamic playlist generation in the context of music recommendation systems. The traditional method of creating playlists frequently depends on immutable standards, like artist or genre, which might not adequately represent the unique and dynamic character of personal preferences. On the other hand, our suggested system makes use of machine learning methods to examine user behavior, preferences, and contextual elements in order to create playlists that are dynamically created and customized to each user’s individual pref
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Holden, Megan, Joanna Marshall, and Andy Lowndes. "Implementing playlist for life in care home settings." FPOP Bulletin: Psychology of Older People 1, no. 160 (2022): 61–62. http://dx.doi.org/10.53841/bpsfpop.2022.1.160.61.

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Personalised, music playlists are a promising non-pharmacological intervention for people living with dementia, however, there are numerous practical barriers to implementing this intervention. This paper will look at the barriers faced by the Durham and Darlington Care Home Liaison Hub when implementing personalised music playlists into care home settings, and how we have overcome them.Those who were at the 2017 FPOP Conference in Durham will remember the inspirational keynote presentation about the work of Playlist for Life, a music and dementia charity. Playlist for Life harnesses the power
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Hagen, Anja Nylund. "The Playlist Experience: Personal Playlists in Music Streaming Services." Popular Music and Society 38, no. 5 (2015): 625–45. http://dx.doi.org/10.1080/03007766.2015.1021174.

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Dimopoulos-Bick, Tara, Kim E. Clowes, Katie Conciatore, Maggie Haertsch, Raj Verma, and Jean-Frederic Levesque. "Barriers and facilitators to implementing playlists as a novel personalised music intervention in public healthcare settings in New South Wales, Australia." Australian Journal of Primary Health 25, no. 1 (2019): 31. http://dx.doi.org/10.1071/py18084.

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Listening to personalised music is a simple and low-cost intervention with expected therapeutic benefits, including reduced agitation, stress responses and anxiety. While there is growing evidence for the use of personalised music as a therapeutic intervention, there has been little investigation into processes and strategies that would support the implementation of playlists. The aim of this study was to identify the perceived barriers and facilitators to implementing personalised playlists on a large scale in public healthcare settings. A mixed-methods approach was used to evaluate the feasi
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Giri, Gst Ayu Vida Mastrika, Made Leo Radhitya, Made Agung Raharja, and I. Wayan Supriana. "SISTEM REKOMENDASI MUSIK BERDASARKAN DATA KONTEKS PADA LISTENING HISTORY MUSIK DAN KETERKAITAN ARTIS INDONESIA." Jurnal RESISTOR (Rekayasa Sistem Komputer) 5, no. 1 (2022): 86–93. http://dx.doi.org/10.31598/jurnalresistor.v5i1.1044.

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A large number of digital music circulates online today. It makes music listeners confused to choose which music is suitable to listen to in certain circumstances or contexts, for example certain time, weather, activity, and desired mood. Playlist creation can make it easy for music listeners to collect their favorite music for a particular context, but creating playlists is time consuming and of course a lot of playlists will have to be created to accommodate all combinations of contexts. In this study, an automated music recommendation system was built using context data consisting of time,
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Dissertations / Theses on the topic "Playlists"

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Costa, Francisco Manuel Ramos. "Geração automática de “playlists” de músicas semelhantes." Master's thesis, Faculdade de Ciências e Tecnologia, 2009. http://hdl.handle.net/10362/10562.

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Dissertação de Mestrado em Engenharia Informática<br>Os avanços tecnológicos em compressão de áudio e em redes de computadores possibilitaram um acréscimo significativo na disponibilidade da música. Lidar com colecções de músicas de grandes dimensões torna a pesquisa de músicas semelhantes num aspecto cada vez mais importante. De forma a comparar músicas, são usadas medidas de distância para medir a semelhança entre duas músicas, com base em descritores extraídos do conteúdo musical. Infelizmente os métodos actuais para o cálculo de semelhança de músicas em grandes quantidades são basta
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Rochow, Kathrin. "“Show me your playlist and I tell you who you are” : An investigation of the social psychological foundation of musical playlists." Thesis, Uppsala universitet, Sociologiska institutionen, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-176519.

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In the age of social networking and music streaming, playlists are a common tool for organizing,sharing or exchanging music in the digital realm. Most research, however, emphasizes mainlypolitical, legal, and ethical constraints of music sharing practices yet, neglects their social impact.Thus, this paper investigates the social-psychological foundation of the playlist and analyses itsfunctionality in establishing social relations and communication. Following the theories of Cooley,Mead, Simmel and Solomon, I conducted and analysed interviews with young Swedish men andwomen, in which they talk
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Bautch, Katie A. "The Effect of Therapeutic Music Playlists on Symptoms of Anxiety: A Clinical Trial." Scholarly Commons, 2021. https://scholarlycommons.pacific.edu/uop_etds/3735.

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This is a pilot study examining the comparative effectiveness of self-administered therapeutic playlists in the treatment of anxiety symptoms. Interventions examined during this study include the musical contour regulation playlist (MCR-P) and a one-directional mood vectoring playlist (MV-P). Measures included the Spielberger State Trait Anxiety Inventory (STAI), and a Likert-type scale for participants to rate their pre- to post-listening levels of anxiety. At the conclusion of the study, participants took part in an interview which were analyzed for data that could help inform for whom the M
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AMARAL, Vítor de Souza. "Geração automática de playlists: entendendo as percepções e expectativas de criadores humanos." Universidade Federal de Campina Grande, 2016. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/677.

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Submitted by Kilvya Braga (kilvyabraga@hotmail.com) on 2018-05-15T13:27:13Z No. of bitstreams: 1 VÍTOR DE SOUZA AMARAL - DISSERTAÇÃO (PPGCC) 2016.pdf: 474505 bytes, checksum: a4f88444155adc7bb62c7035f928a20b (MD5)<br>Made available in DSpace on 2018-05-15T13:27:13Z (GMT). No. of bitstreams: 1 VÍTOR DE SOUZA AMARAL - DISSERTAÇÃO (PPGCC) 2016.pdf: 474505 bytes, checksum: a4f88444155adc7bb62c7035f928a20b (MD5) Previous issue date: 2016<br>Capes<br>Uma playlist pode ser definida como qualquer sequência de músicas para ser executada tipicamente de forma ordenada sem que seja necessário ao usuá
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Boone, Will Katz Mark. "Composing playlists, conducting streams the life of classical music in the internet age /." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1819.

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Thesis (M.A.)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Dec. 11, 2008). "... in partial fulfillment of the requirements for the degree of Master of Arts in the Department of Music." Discipline: Music; Department/School: Music.
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Bautch, Katie A. "Feasibility and Effectiveness of Self-Administered Mood Vectoring Playlists in the Treatment of Anxiety Symptoms." Scholarly Commons, 2021. https://scholarlycommons.pacific.edu/uop_etds/3736.

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This is a mixed-methods pre-experimental clinical effectiveness trial that examines the effectiveness of a self-administered one-directional mood vectoring playlist in the management of symptoms of anxiety. This study used the Spielberger State Trait Anxiety Inventory, as well as a self-report Likert-type scale where participants rated their anxiety symptom severity, to explore the impact of the playlist intervention. Qualitative interviews sought to identify themes common among participants who were daily high responders and those who were daily low responders to the intervention in order to
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Dutra, Alex Amorim. "Explorando dados públicos de programação de rádios e playlists na web para recomendação em música." reponame:Repositório Institucional da UFOP, 2014. http://www.repositorio.ufop.br/handle/123456789/4214.

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Programa de Pós-Graduação em Ciência da Computação. Departamento de Ciência da Computação, Instituto de Ciências Exatas e Biológicas, Universidade Federal de Ouro Preto.<br>Submitted by Oliveira Flávia (flavia@sisbin.ufop.br) on 2015-01-12T15:49:36Z No. of bitstreams: 2 license_rdf: 22190 bytes, checksum: 19e8a2b57ef43c09f4d7071d2153c97d (MD5) DISSERTAÇÃO_ExplorandoDadosPúblicos.pdf: 1429209 bytes, checksum: 6d9ace1ed2b65c1e0e50def4785c2592 (MD5)<br>Approved for entry into archive by Gracilene Carvalho (gracilene@sisbin.ufop.br) on 2015-01-15T17:22:26Z (GMT) No. of bitstreams: 2 license_rdf:
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Aalto, Erik. "Learning Playlist Representations for Automatic Playlist Generation." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172845.

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Spotify is currently the worlds leading music streaming ser-vice. As the leader in music streaming the task of providing listeners with music recommendations is vital for Spotify. Listening to playlists is a popular way of consuming music, but traditional recommender systems tend to fo-cus on suggesting songs, albums or artists rather than pro-viding consumers with playlists generated for their needs. This thesis presents a scalable and generalizeable approach to music recommendation that performs song selection for the problem of playlist generation. The approach selects tracks related to a p
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Meadley, Sam. "Automatic playlist generation using measurements of musical similarity /." Leeds : University of Leeds, School of Computer Studies, 2008. http://www.comp.leeds.ac.uk/fyproj/reports/0708/Meadley.pdf.

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Fields, Benjamin. "Contextualize your listening : the playlist as recommendation engine." Thesis, Goldsmiths College (University of London), 2011. http://research.gold.ac.uk/6477/.

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It is not hyperbole to note that a revolution has occurred in the way that we as a society distribute data and information. This revolution has come about through the confluence of Web-related technologies and the approaching universal adoption of internet connectivity. Add to this mix the normalised use of lossy compression in digital music and the increase in digital music download and streaming services; the result is an environment where nearly anyone can listen to nearly any piece of music nearly anywhere. This is in many respects the pinnacle in music access and availability. Yet, a list
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Books on the topic "Playlists"

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Mark, Ellingham, ed. The rough guide book of playlists. 2nd ed. Rough Guides, 2006.

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Mark, Ellingham, ed. The rough guide book of playlists. Rough Guides, 2005.

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Whitburn, Joel. Joel Whitburn's top pop playlists 1955-1969. Record Research, 2014.

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Iles, Anthony, ed. Agit Disco: A project by Stefan Szczelkun. Mute Books, 2012.

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Nathan, Stocker, ed. Infinite playlists: How to have conversations (not conflict) with your kid about music. Kregel Publications, 2010.

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Nicolas, Bourriaud, and Musée d'art et d'essai (Paris, France), eds. Playlist. Palais de Tokyo, 2004.

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Gomez, Selena. Disney channel playlist. Walt Disney Records, 2009.

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Schreiber, Joe. Perry's Killer Playlist. Houghton Mifflin, 2012.

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Trawny, Peter. kamikaze musike: Playlist. Matthes & Seitz Berlin, 2019.

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Sansone, Hernán. 33RPM: Playlist revolucionario. La Silueta Ediciones, 2016.

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Book chapters on the topic "Playlists"

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Amos, Jonny. "Pitching for Playlists." In The Music Business for Music Creators. Focal Press, 2024. http://dx.doi.org/10.4324/9781003452119-28.

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Gascón, Valeria. "Playlists, connection, and Covid." In Music and Social Inclusion. Routledge, 2022. http://dx.doi.org/10.4324/9781003188667-8.

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Hahn, Clemens, Stéphane Turlier, Thorsten Liebig, Sascha Gebhardt, and Christopher Roelle. "Metadata Aggregation for Personalized Music Playlists." In HCI in Work and Learning, Life and Leisure. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16607-5_29.

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Papreja, Piyush, Hemanth Venkateswara, and Sethuraman Panchanathan. "Representation, Exploration and Recommendation of Playlists." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43887-6_50.

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Amos, Jonny. "The Algorithmic Scaffold of Spotify and Its Playlists." In The Music Business for Music Creators. Focal Press, 2024. http://dx.doi.org/10.4324/9781003452119-27.

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Delcluze, Mathieu, Antoine Khoury, Clémence Vast, et al. "Text2Playlist: Generating Personalized Playlists from Text on Deezer." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88720-8_27.

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King, James, and Vaiva Imbrasaitė. "Generating Music Playlists with Hierarchical Clustering and Q-Learning." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16354-3_34.

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Helmholz, Patrick, Sebastian Vetter, and Susanne Robra-Bissantz. "AmbiTune: Bringing Context-Awareness to Music Playlists while Driving." In Advancing the Impact of Design Science: Moving from Theory to Practice. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06701-8_32.

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Berger, Arne, Robert Knauf, Maximilian Eibl, and Aaron Marcus. "Moody Mobile TV: Exploring TV Clips with Personalized Playlists." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21675-6_62.

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James Walsh, Michael. "User-made playlists and the shaping of social interaction." In Streaming Sounds. Routledge, 2024. http://dx.doi.org/10.4324/9781003273363-2.

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Conference papers on the topic "Playlists"

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Shiralaskar, Hrishikesh, and Sameer Mendhe. "Beyond Playlists: AI-Driven Emotion-Based Music Recommendation Systems." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10968205.

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Awasthi, Parth, Bharti Sahu, Sarmista Rath, Vinit Mittal, and Lavesh Bhardwaj. "Dynamic Playlist Generation Using AI." In 2024 Second International Conference on Advanced Computing & Communication Technologies (ICACCTech). IEEE, 2024. https://doi.org/10.1109/icacctech65084.2024.00017.

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Cheng, Chun-Han, Ting-Yu Wei, and Homer H. Chen. "Playlist Continuation of Cold-Start Songs." In 2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2024. http://dx.doi.org/10.1109/mipr62202.2024.00029.

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Donnelly, Patrick, and Shaurya Gaur. "Mood Dynamic Playlist:Interpolating a musical path between emotions using a KNN algorithm." In Human Interaction and Emerging Technologies (IHIET-AI 2022) Artificial Intelligence and Future Applications. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe100893.

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We often to listen to music for its power to change our emotions. Whether selecting music for concentration, tunes for dancing, or lullabies for falling asleep, people often select music based on their desired mood or activity. We propose a method for automatically generating musical playlists that takes the listener on an emotional journey. We represent a playlist as a path of songs through the arousal-valence circumplex space, using existing datasets of songs annotated with affect values. Given a starting and desired affective state, we employ a K-nearest neighbor approach to choose songs th
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Uwajima, Yuki, and Wonseok Yang. "Effect of freedom of customization on psychological ownership." In 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005130.

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The digitization of tangible assets, driven by advancements in Information and Communication Technology (ICT), not only fosters the emergence of new products, services, and markets but also significantly transforms consumer behavior from ownership-based to access-based consumption. This shift in consumption models can threaten or transfer consumers' psychological sense of ownership, presenting new opportunities for preservation. Particularly in streaming services such as Spotify, YouTube, and Apple Music, access-based content consumption may lead to a potential decrease in the psychological se
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Lehtiniemi, Arto, and Jukka Holm. "Easy access to recommendation playlists." In the 10th International Conference. ACM Press, 2011. http://dx.doi.org/10.1145/2107596.2107607.

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Casalnova, Claire, Calista Gasper, Grace Lombardi, and Daryl Johnson. "Covert Communications via Spotify Playlists." In The 8th World Congress on Electrical Engineering and Computer Systems and Science. Avestia Publishing, 2022. http://dx.doi.org/10.11159/cist22.110.

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James, Helen. "VENT. REFLECT. CONNECT (a silent disco to rage, reflect, and heal)." In 10th Annual International Weight Stigma Conference. Weight Stigma Conference, 2024. https://doi.org/10.31076/2024.s10.

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The emotional impact of working in weight stigma spaces can be profound. Even at an event where most people ‘get it,’ this work can take a toll. I would like us to work together to create three playlists on the themes of Vent, Reflect, and Connect. VENT: music that can honour frustration, anger, rage REFLECT: music that can inspire, comfort, be reflective: CONNECT: music that can unify, lift, heal How it will work: Conference attendees can contribute to the playlists using Spotify or Google forms. I will set up the link and instructions one week before the start of the conference. Online deleg
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Romero, Raphaël, and Tijl De Bie. "Embedding-based next song recommendation for playlists." In ESANN 2022 - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Ciaco - i6doc.com, 2022. http://dx.doi.org/10.14428/esann/2022.es2022-28.

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Subramaniam, Ganeshsiva, Janhavi Verma, Nikhil Chandrasekhar, Narendra K. C., and Koshy George. "Generating Playlists on the Basis of Emotion." In 2018 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2018. http://dx.doi.org/10.1109/ssci.2018.8628673.

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