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Sophie O. Freeman

dblp:344/3229 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
0000-0003-1003-6499ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Recommender systems · 100%
Human-computer interaction and pervasive computing
1 paper
Human-AI interaction · 100%
Computer graphics and multimedia
1 paper
Multimedia systems and quality of experience · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Recommender systems
music recommendation
0.712023
Personalised But Impersonal: Listeners' Experiences of Algorithmic Curation on Music Streaming Services · CHI 2023
Human-AI interaction
algorithmic experience
0.712023
Personalised But Impersonal: Listeners' Experiences of Algorithmic Curation on Music Streaming Services · CHI 2023
Multimedia systems and quality of experience › multimedia streaming
music streaming
0.212023
Personalised But Impersonal: Listeners' Experiences of Algorithmic Curation on Music Streaming Services · CHI 2023

Methods — techniques the papers use, named apart from their topics

participant observation · 2.0interview study · 2.0design workshop · 2.0
YearPublicationVenuePosition
2023 Personalised But Impersonal: Listeners' Experiences of Algorithmic Curation on Music Streaming Services
abstract
The consumption of music is increasingly reliant on the personalisation, recommendation, and automated curation features of music streaming services. Using algorithm experience (AX) as a lens, we investigated the user experience of the algorithmic recommendation and automated curation features of several popular music streaming services. We conducted interviews and participant-observation with 15 daily users of music streaming services, followed by a design workshop. We found that despite the utility of increasingly algorithmic personalisation, listeners experienced these algorithmic and recommendation features as impersonal in determining their background listening, music discovery, and playlist curation. While listener desire for more control over recommendation settings is not new, we offer a number of novel insights about music listening to nuance this understanding, particularly through the notion of vibe.
Sophie O. Freeman, Martin R. Gibbs, Bjørn Nansen
CHI1