SpotifyExplained: User-centric Mobile Application for Music Exploration

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10468870" target="_blank" >RIV/00216208:11320/23:10468870 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1145/3563359.3597392" target="_blank" >https://doi.org/10.1145/3563359.3597392</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3563359.3597392" target="_blank" >10.1145/3563359.3597392</a>

Result language

angličtina

Original language name

SpotifyExplained: User-centric Mobile Application for Music Exploration

Original language description

Many music streaming services, such as Spotify, contain a large volume of heavy users, whose user profiles may contain tens to hundreds artists or hundreds to thousands favorite tracks. For those users, it may be difficult to understand, what data the service collected about them, what is the base for its automated decisions (e.g., recommendations) and why are particular items suggested to them. This may decrease user&apos;s willingness to explore the suggested content and may eventually lead to the decrease of user satisfaction and trust. In this demo, we present SpotifyExplained Android application, which is built on top of Spotify API and aims to bridge the aforementioned understandability gap. Specifically, the application contains several tunable views on users&apos; music profiles and visually explain the connections between both the already known content as well as newly suggested items.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA22-21696S" target="_blank" >GA22-21696S: Deep Visual Representations of Unstructured Data</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization

ISBN

978-1-4503-9891-6

ISSN

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e-ISSN

—

Number of pages

4

Pages from-to

92-95

Publisher name

ACM

Place of publication

New York, NY, USA

Event location

Limassol, Cyprus

Event date

Jun 26, 2023

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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