A Rule-Based Approach for Detecting Location Leaks of Short Text Messages
Hoang-Quoc Nguyen-Son, Minh–Triet Tran, Hiroshi Yoshiura, Noboru Sonehara, Isao Echizen · Lecture notes in business information processing · 2015
As of today, millions of people share messages via online social networks, some of which probably contain sensitive information. An adversary can collect these freely available messages and specifically analyze them for privacy leaks, such as the users’ location. Unlike other approaches that try to detect these leaks using complete message streams, we put forward a rule-based approach that works on single and very short messages to detect location leaks. We evaluated our approach based on 2817 tweets from the Tweets2011 data set. It scores significantly better (accuracy = 84.95 %) on detecting whenever a message reveals the user’s location than a baseline using machine learning and three extensions using heuristic. Advantages of our approach are not only to apply for online social network messages but also to extend for other areas (such as email, military, health) and for other languages.