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Rethinking location sharing: exploring the implications of social-driven vs. purpose-driven location sharing

Published: 26 September 2010 Publication History

Abstract

The popularity of micro-blogging has made general-purpose information sharing a pervasive phenomenon. This trend is now impacting location sharing applications (LSAs) such that users are sharing their location data with a much wider and more diverse audience. In this paper, we describe this as social-driven sharing, distinguishing it from past examples of what we refer to as purpose-driven location sharing. We explore the differences between these two types of sharing by conducting a comparative two-week study with nine participants. We found significant differences in terms of users' decisions about what location information to share, their privacy concerns, and how privacy-preserving their disclosures were. Based on these results, we provide design implications for future LSAs.

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    cover image ACM Conferences
    UbiComp '10: Proceedings of the 12th ACM international conference on Ubiquitous computing
    September 2010
    366 pages
    ISBN:9781605588438
    DOI:10.1145/1864349
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 26 September 2010

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    Author Tags

    1. location sharing
    2. place naming
    3. privacy

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    Ubicomp '10
    Ubicomp '10: The 2010 ACM Conference on Ubiquitous Computing
    September 26 - 29, 2010
    Copenhagen, Denmark

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    UbiComp '10 Paper Acceptance Rate 39 of 202 submissions, 19%;
    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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    • (2022)Tailor My ZwiftProceedings of the ACM on Human-Computer Interaction10.1145/35467516:MHCI(1-23)Online publication date: 20-Sep-2022
    • (2022)#34;You have been in Close Contact with a Person Infected with COVID-19 and you may have been Infected#34;Proceedings of the ACM on Human-Computer Interaction10.1145/35467396:MHCI(1-27)Online publication date: 20-Sep-2022
    • (2022)NotiBike: Assessing Target Selection Techniques for Cyclist Notifications in Augmented RealityProceedings of the ACM on Human-Computer Interaction10.1145/35467326:MHCI(1-24)Online publication date: 20-Sep-2022
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