Publikation: Digitally nudging users to explore off-...
Stammdaten
Titel: | Digitally nudging users to explore off-profile recommendations: here be dragons |
Untertitel: | |
Kurzfassung: | In many application domains of recommender systems, e.g., on media streaming sites, one main goal of the provider of the recommendation service is to increase the engagement of users by helping them discover new types of content they like. Standard collaborative filtering algorithms by design often lead to a certain level of discovery. Nonetheless, in certain domains, it may be helpful to more actively promote content to users beyond their past preference profile (“off-profile”) and thereby help users explore new content. However, when showing such off-profile content to users in combination with more familiar content, the new content items may be overlooked. In this research, we explore to what extent digital nudging, i.e., subtly directing user choices in a specific direction, can help to raise the attention and interest of users for off-profile content. We conducted a user study ($$N=1064$$ N = 1064 ) on a real-world social book recommendation app. We find that users who are nudged towards recommended books of their non-preferred genres significantly more often put these off-profile books on their reading lists, thus confirming the effectiveness of digital nudging in this application. However, we also found that digital nudges may negatively impact the users’ beliefs and attitudes towards the system and a more limited intention to use the system in the future. As a result, we find that digital nudging in recommendations, while effective in the short run, must be done with due care, keeping an eye on the overall quality perceptions by users and potentially harmful long-term effects. |
Schlagworte: | Computer Science Applications, Human-Computer Interaction, Education |
Publikationstyp: | Beitrag in Zeitschrift (Autorenschaft) |
Erscheinungsdatum: | 04.10.2023 (Online) |
Erschienen in: |
User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
(
Springer Verlag GmbH;
)
zur Publikation |
Titel der Serie: | - |
Bandnummer: | - |
Heftnummer: | - |
Erstveröffentlichung: | Ja |
Version: | - |
Seite: | S. 1 - 41 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 04.10.2023 |
ISBN (e-book): | - |
eISSN: | 1573-1391 |
DOI: | http://dx.doi.org/10.1007/s11257-023-09378-7 |
Homepage: | - |
Open Access |
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AutorInnen
Gabrielle Alves (extern) |
Dietmar Jannach (intern) |
Rodrigo Ferrari de Souza (extern) |
Daniela Damian (extern) |
Marcelo Garcia Manzato (extern) |
Zuordnung
Organisation | Adresse | ||||
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Fakultät für Technische Wissenschaften
Institut für Artificial Intelligence und Cybersecurity
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AT - A-9020 Klagenfurt |
Kategorisierung
Sachgebiete | |
Forschungscluster |
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Zitationsindex |
Informationen zum Zitationsindex: Master Journal List
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Peer Reviewed |
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Publikationsfokus |
Klassifikationsraster der zugeordneten Organisationseinheiten:
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Arbeitsgruppen |
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Kooperationen
Organisation | Adresse | ||
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University of Victoria
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CA
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Universidade de São Paulo
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BR
São Paulo |
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(Achtung: Externe Aktivitäten werden im Suchergebnis nicht mitangezeigt)
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