Effective privacy management requires that mobile systems" users be able to make informed privacy decisions as their experience and knowledge of a system progresses. Prior work has shown that making such privacy decisions is a difficult task for users because systems do not provide support for awareness, visibility and accountability when sharing privacy-sensitive information. This paper reports results of our investigation into the efficacy of realtime feedback as a mechanism for incorporating these features of social translucence in location-sharing applications, in order to help users make better privacy decisions. We explored the role of real-time feedback in the context of Buddy Tracker, a mobile location-sharing application. Our work focuses on ways in which real-time feedback affects people"s behaviour in order to identify the main criteria for acceptance of this technology. Based on the data from a three week field trial of Buddy Tracker, a focus group session, and interviews, we found that when using a system that provided real-time feedback, people were more accountable for their actions and reduced the number of unreasonable location requests. We have used the results of our study to propose highlevel design criteria for incorporating real-time feedback into information sharing applications in a manner that ensures social acceptance of the technology.  Categories and Subject Descriptors Design, Experimentation, Human Factors. Feedback, mobile computing, location based services, privacy management, social translucence. Many studies have shown that users are not very good at understanding the future value of keeping personal information private [1, 2] . Some solutions involving location privacy policies have been suggested (e.g., [3] ). However, prior research shows that end-users have difficulties in expressing and setting their privacy preferences, and their privacy policies change only marginally, unless they are given privacy tools that help them understand future implications of their privacy-related choices [2, 4] . Moreover, setting privacy rules is a time-consuming process, which many people are unwilling to do until their privacy is violated. We see this as a strong motivation to design tools that help users to make informed privacy decisions as their experience and knowledge of a system progress. In the spirit of Palen and Dourish [5], we propose to build privacy-sensitive systems supporting the continual and selective disclosure of personal information by providing real-time feedback as the method of informing users about how their location information is being used. In our work we define feedback to be the notification of information disclosure, where the notification specifies what information about the person is disclosed when and to whom. This definition is drawn from the work of Bellotti and Sellen who considered feedback as "informing people when and what information about them is being captured and to whom the information is being made available" [6] . While such feedbackoriented support for privacy management has been studied on conventional (large screen) computers [7, 8] , innovations are needed for mobile devices. Therefore we decided to explore the role of real-time feedback in managing privacy in mobile location-sharing applications. In this paper we present a location-sharing service grounded on the concept of socially translucent systems proposed by Erickson and Kellogg [9]. Translucency is achieved by real-time feedback providing awareness and visibility in the form of ad-hoc warnings displayed on, or generated by, the mobile device. Obviously, information about who has accessed one"s location information might have a positive effect, i.e. improving the comfort of using location-sharing technologies, openness or fewer privacy concerns [7] . However, our preliminary results suggest that this is not always the case, especially from the perspective of data requesters. Our field trial with the real-time feedback feature showed that people were more accountable for their actions if they knew that the data owner would be notified of their request. This supports the third characteristic of socially translucent systems: accountability. Providing feedback to those whose location is being checked resulted in better awareness and understanding of the location requests made by others. This resulted in location requests being made only when the requester has good reason to do so. We explore the role of real-time feedback in privacy management in the context of Buddy Tracker, a mobile location-sharing service we developed, by asking the following questions:
Jedrzejczyk et al. REF explored the realtime feedback effects on users' behaviors by implementing a location-sharing social app Buddy Tracker.
On The Impact of Real-Time Feedback on Users' Behaviour in Mobile Location-Sharing Applications
SOUPS
Computer Science