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Modelling perceived risks to personal privacy from location disclosure on online social networks

Alrayes, Fatma, Abdelmoty, Alia and Theodorakopoulos, Georgios 2020. Modelling perceived risks to personal privacy from location disclosure on online social networks. International Journal of Geographical Information Science 34 (1) , pp. 150-176. 10.1080/13658816.2019.1654109

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As users increasingly rely on online social networks for their communication activities, personal location data processing through such networks poses significant risks to users’ privacy. Location tracks can be mined with other shared information to extract rich personal profiles. To protect users’ privacy, online social networks face the challenge of ensuring transparent communication to users of how their data are processed, and explicitly obtaining users’ informed consent for the use of this data. In this paper, we explore the complex nature of the location disclosure problem and its risks to personal privacy. We evaluate, with an experiment involving 715 participants, the contributing factors to the perception of such risks with scenarios that mimic (a) realistic modes of interaction, where users are not fully aware of the extent of their location-related data being processed, and (b) with devised scenarios that deliberately inform users of the data they are sharing and its visibility to others. The results are used to represent the users’ perception of privacy risks when sharing their location information online and to derive a possible model of privacy risks associated with this sharing behaviour. Such a model can inform the design of privacy-aware online social networks to improve users’ trust and to ensure compliance with legal frameworks for personal privacy.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Taylor & Francis
ISSN: 1365-8816
Date of First Compliant Deposit: 2 September 2019
Date of Acceptance: 5 August 2019
Last Modified: 24 Nov 2020 22:49

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