Detecting unintentional information leakage in social media news comments

This paper is concerned with unintentional information leakage (UIL) through social networks, and in particular, Facebook Organizations often use forms of self censorship in order to maintain security. Non-identification of individuals, products, or places is seen as a sufficient means of information protection. A prime example is the replacement of a name with a supposedly non-identifying initial. This has traditionally been effective in obfuscating the identity of military personnel, protected witnesses, minors, victims or suspects who need to be granted a level of protection through anonymity. We challenge the effectiveness of this form of censorship in light of current uses and ongoing developments in Social Networks showing that name-obfits cation mandated by court or military order can be systematically compromised through the unintentional actions of public social network commenters. We propose a qualitative method for recognition and characterization of UIL followed by a quantitative study that automatically detects UIL comments.