A New Method for Measuring Individual Importance in Social Network Analysis

Nowadays, centrality computing is the most common measure for finding important actors in Social Network Analysis (SNA). In this paper, we proposed a new method SHITS applied to social networks to find relatively important actors. This new method assigns two attribute values to each actor, namely SAuthority and SHub, among which SAuthority denotes the value themselves and SHub evaluates the intermediary functions they have. It can discover more valuable and useful information than traditional ways. And we also use newsmth BBS as an example to specify SHITS. Finally the experiment results show the method can discover some hidden information which verified our algorithm is validated.