Link Prediction in Highly Fractional Data Sets

Extremist organizations all over the world increasingly use online social networks as a communication media for recruitment and planning. As such, online social networks are also a source of information utilized by intelligence and counter terror organizations investigating the relationships between suspected individuals. Unfortunately, the data mined from open sources is usually far from being complete due to the efforts of suspected and known terrorists to hide their relationships. One of the methods used to uncover missing information in social networks is referred to as link prediction. We use link prediction methods solely based on network structure analysis to infer hidden relationships among individuals and investigate their effectiveness in fractional datasets. Experiments performed on a number of closed communities extracted from organizational and public social networks show that structural link prediction retains its effectiveness even when large parts of the original social network are hidden.