YOURPRIVACYPROTECTOR, A recommender system for privacy settings in social networks

TL;DR

YourPrivacyProtector is a machine learning-based recommender system designed to help social network users understand and choose appropriate privacy settings, addressing user awareness and usability issues.

Contribution

The paper introduces a novel recommender system that assists users in understanding and selecting privacy options in social networks using simple machine learning techniques.

Findings

Empirical validation on Facebook user groups shows effectiveness.

Users improved understanding of privacy settings.

Recommender system increased appropriate privacy option usage.

Abstract

Ensuring privacy of users of social networks is probably an unsolvable conundrum. At the same time, an informed use of the existing privacy options by the social network participants may alleviate - or even prevent - some of the more drastic privacy-averse incidents. Unfortunately, recent surveys show that an average user is either not aware of these options or does not use them, probably due to their perceived complexity. It is therefore reasonable to believe that tools assisting users with two tasks: 1) understanding their social net behavior in terms of their privacy settings and broad privacy categories, and 2)recommending reasonable privacy options, will be a valuable tool for everyday privacy practice in a social network context. This paper presents YourPrivacyProtector, a recommender system that shows how simple machine learning techniques may provide useful assistance in these two tasks to Facebook users. We support our claim with empirical results of application of YourPrivacyProtector to two groups of Facebook users.