Automatic Extraction of Concealed Relations from Email

People interact with each other for various reasons. Based on the purpose of the relationship, these interactions exhibit certain characteristics. One such important characteristic is that of concealment. Concealed relations can often be a source of interest especially in the domain of counterterrorism where relations fostering malicious activities tend to be secretive or concealed from the general public. In this paper we propose a technique for extracting concealed relations from social network data. The technique analyzes actors’ perceptions regarding other actors’ social interactions and requires that they can be constructed from the social network data. One popular communication medium for which this can be done efficiently is electronic mail. The proposed technique uses the popular and robust tf-idf measure from the information retrieval literature to quantify the concept of concealment. We present experimental results from the Enron email corpus.