A cross-cultural analysis of trust in recommender systems

Shlomo Berkovsky; Ronnie Taib; Yoshinori Hijikata; Pavel Braslavsku; Bart Knijnenburg

doi:10.1145/3209219.3209251

A cross-cultural analysis of trust in recommender systems

Shlomo Berkovsky, Ronnie Taib, Yoshinori Hijikata, Pavel Braslavsku, Bart Knijnenburg

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

12 Citations (Scopus)

Abstract

User system trust is critical to the uptake of recommendations, and several factors of trust have been identified and compared. In this paper we present a cross-cultural, crowdsourced study examining user perceptions of nine factors of trust and link the observed differences to trust development processes and cultural dimensions. While some factors consistently instil trust, others are preferred only in certain countries. Our findings and the discovered links are important for design of trusted recommender systems.

Original language	English
Title of host publication	UMAP'18, Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization
Place of Publication	New York, NY
Publisher	Association for Computing Machinery (ACM)
Pages	285-289
Number of pages	5
ISBN (Electronic)	9781450355896
DOIs	https://doi.org/10.1145/3209219.3209251
Publication status	Published - 3 Jul 2018
Externally published	Yes
Event	26th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2018 - Singapore, Singapore Duration: 8 Jul 2018 → 11 Jul 2018

Conference

Conference	26th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2018
Country/Territory	Singapore
City	Singapore
Period	8/07/18 → 11/07/18

Keywords

Recommender systems
user-system trust
presentation of recommendations
cross-cultural comparison
user study

Access to Document

10.1145/3209219.3209251

Cite this

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title = "A cross-cultural analysis of trust in recommender systems",

abstract = "User system trust is critical to the uptake of recommendations, and several factors of trust have been identified and compared. In this paper we present a cross-cultural, crowdsourced study examining user perceptions of nine factors of trust and link the observed differences to trust development processes and cultural dimensions. While some factors consistently instil trust, others are preferred only in certain countries. Our findings and the discovered links are important for design of trusted recommender systems.",

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Berkovsky, S, Taib, R, Hijikata, Y, Braslavsku, P & Knijnenburg, B 2018, A cross-cultural analysis of trust in recommender systems. in UMAP'18, Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery (ACM), New York, NY, pp. 285-289, 26th International Conference on User Modeling, Adaptation, and Personalization, UMAP 2018, Singapore, Singapore, 8/07/18. https://doi.org/10.1145/3209219.3209251

A cross-cultural analysis of trust in recommender systems. / Berkovsky, Shlomo; Taib, Ronnie; Hijikata, Yoshinori et al.
UMAP'18, Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization. New York, NY: Association for Computing Machinery (ACM), 2018. p. 285-289.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Hijikata, Yoshinori

AU - Braslavsku, Pavel

AU - Knijnenburg, Bart

PY - 2018/7/3

Y1 - 2018/7/3

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AB - User system trust is critical to the uptake of recommendations, and several factors of trust have been identified and compared. In this paper we present a cross-cultural, crowdsourced study examining user perceptions of nine factors of trust and link the observed differences to trust development processes and cultural dimensions. While some factors consistently instil trust, others are preferred only in certain countries. Our findings and the discovered links are important for design of trusted recommender systems.

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KW - presentation of recommendations

KW - cross-cultural comparison

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BT - UMAP'18, Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization

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ER -

A cross-cultural analysis of trust in recommender systems

Abstract

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Keywords

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