Evaluating PIT-OSN 1 in inspecting the privacy levels of an online social network

Abstract

In the last few years, Online Social Networks (OSNs) have experienced a growth in their number of users, becoming an increasingly embedded part of people's daily lives. Privacy expectations in OSNs are getting smaller as more members begin to face potential privacy problems when interacting with these systems. Inspections methods can be an effective alternative for addressing privacy problems because they allow detecting a possible defect that could be causing the system to behave in an undesirable way. Based on that, a set of privacy inspection techniques called PIT-OSN (Privacy Inspection Techniques for Online Social Network) was proposed. This paper focuses on one of these techniques (the PIT-OSN 1), which supports the inspection of the privacy levels in an OSN. The goal of this paper is to present the evaluation of PIT-OSN 1, through an empirical study, which collected quantitative and qualitative data. Results obtained from the analysis indicate that the technique assists nonexpert inspectors detecting privacy problems effectively and that it was considered easy to use and useful by the participants of the study. Finally, the qualitative analysis points out relevant improvement opportunities in PIT-OSN 1.