SEmantic Context Aware Network Tools (SECANT)

Social network analysis has become one of the most powerful analytic tools in both private and government sectors and a key source of information on individuals and groups. Recently, social media arose as an important source for social network data in both sectors. Unfortunately, theoretically motivated approaches to social network analysis have not been able to keep pace with the new informational character of social media. Social media offers a previously unheard of volume and variety of data making possible richer analyses, but also introducing greater levels of complexity and noise. We propose a system called SEmantic Context Aware Network Tools (SECANT). SECANT is motivated by the observation that traditional research methodologies in the fields of structural network analysis, sociologically and psychologically theory and content mining each contain gaps the other fields can fill. The goal of SECANT is to enable hybrid methodologies from these fields that will produce analytic tools which yield more meaningful and relevant results. SECANT blends the scalability of traditional SNA with sociology"s awareness of social context, and content mining"s awareness of semantic context of its base fields to accomplish this goal.