Developing privacy guidelines for social location disclosure applications and services

Abstract

In this article, we describe the design process of Reno, a location-enhanced, mobile coordination tool and person finder. The design process included three field experiments: a formative Experience Sampling Method (ESM) study, a pilot deployment and an extended user study. These studies were targeted at the significant personal security, privacy and data protection concerns caused by this application. We distil this experience into a small set of guidelines for designers of social mobile applications and show how these guidelines can be applied to a different application, called Boise. These guidelines cover issues pertaining to personal boundary definition, control, deception and denial, and group vs. individual communication. We also report on lessons learned from our evaluation experience, which might help practitioners in designing novel mobile applications, including the choice and characterization of users for testing security and privacy features of designs, the length of learning curves and their effect on evaluation and the impact of peculiar deployment circumstances on the results of these finely tuned user studies.