Identifying focal patterns in social networks

Abstract

Identifying authoritative individuals is a well-known approach in extracting actionable knowledge, known as “Knowledge Representation”, in a social network. Previous researches suggest measures to identify influential individuals, however, such individuals might not represent the appropriate context (relationships, interactions, etc.). For example, it is nearly an impossible task for a single individual to organize a mass protest of the scale of Occupy Wall Street. Similarly, other events such as the Arab Spring, coordinating crisis responses for natural disasters (e.g., the Haiti earthquake), or even organizing flash mobs would require a key set of individuals rather than a single or the most authoritative one. These events demonstrate the need and importance of examining influential structures rather than single individuals in social networks. A new methodology is proposed to identify such influential structures and recognizing their importance. The proposed methodology is evaluated empirically with real-world data from NIST's Tweets2011 corpus. We also introduce a novel and objective evaluation strategy to ascertain the efficacy of the focal patterns. Challenges with future research directions are outlined.