Predicting Privacy Attitudes Using Phone Metadata (1604.04167v1)

Abstract: With the increasing usage of smartphones, there is a corresponding increase in the phone metadata generated by individuals using these devices. Managing the privacy of personal information on these devices can be a complex task. Recent research has suggested the use of social and behavioral data for automatically recommending privacy settings. This paper is the first effort to connect users' phone use metadata with their privacy attitudes. Based on a 10-week long field study involving phone metadata collection via an app, and a survey on privacy attitudes, we report that an analysis of cell phone metadata may reveal vital clues to a person's privacy attitudes. Specifically, a predictive model based on phone usage metadata significantly outperforms a comparable personality features-based model in predicting individual privacy attitudes. The results motivate a newer direction of automatically inferring a user's privacy attitudes by looking at their phone usage characteristics.