Skip to content

Research at St Andrews

The effect of privacy concerns on privacy recommenders

Research output: Chapter in Book/Report/Conference proceedingConference contribution


School/Research organisations


Location-sharing services such as Facebook and Foursquare/Swarm have become increasingly popular, due to the ease at which users can share their locations, and participate in services, games and other applications that leverage these locations. But it is important for people who use these services to configure appropriate location-privacy preferences so that they can control to whom they want to share their location information. Manually configuring these preferences may be burdensome and confusing, and so location-privacy preference recommenders based on crowd sourcing preferences from other users have been proposed. Whether people will accept the recommended preferences acquired from other users, who they may not know or trust, has not, however, been investigated.In this paper, we present a user experiment (n=99) to explore what factors influence people’s acceptance of location privacy preference recommenders. We find that 44% of our participants have privacy concerns about such recommenders. These concerns are shown to have a negative effect (p <0.001) on their acceptance of the recommendations and their satisfaction about their choices. Furthermore, users’ acceptance of recommenders varies according to both context and recommendations being made. Our findings are potentially useful to designers of location-sharing services and privacy recommenders.


Original languageEnglish
Title of host publicationIUI '16 Proceedings of the 21st International Conference on Intelligent User Interfaces
Place of PublicationNew York
Number of pages10
ISBN (Print)9781450341370
Publication statusPublished - 7 Mar 2016
EventACM IUI 2016 - Sonoma Rennaissance Resort and Spa, California, Sonoma, United States
Duration: 7 Mar 201610 Mar 2016


ConferenceACM IUI 2016
CountryUnited States
Internet address

    Research areas

  • Location-based services, Location-sharing services, Privacy preferences, Recommender systems, User acceptance

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. A robust reputation-based location-privacy recommender system using opportunistic networks

    Zhao, Y., Ye, J. & Henderson, T., 1 Dec 2016, Proceedings of The 8th EAI International Conference on Mobile Computing, Applications and Services. ACM

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  2. Privacy-Aware Location Privacy Preference Recommendations

    Zhao, Y., Ye, J. & Henderson, T., 2 Dec 2014, Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous). p. 120-129

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  3. Recommending Location Privacy Preferences in Ubiquitous Computing

    Zhao, Y., Ye, J. & Henderson, T., 23 Jul 2014.

    Research output: Contribution to conferencePoster

  4. Co-Creating Autonomy: Group data protection and individual self-determination within a data commons

    Wong, J. & Henderson, T., 2 Feb 2020, (Accepted/In press) Proceedings of the 15th International Digital Curation Conference.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  5. Lifelong learning in sensor-based human activity recognition

    Ye, J., Dobson, S. A. & Zambonelli, F., 18 Nov 2019, In : IEEE Pervasive Computing. 18, 3, p. 49-58 10 p.

    Research output: Contribution to journalArticle

ID: 238216551