Interaction coherence analysis (ICA) attempts to accurately identify and construct interaction networks by using various features and techniques. It is useful to identify user roles, user's social and information value, as well as the social network structure of Dark Web communities. In this study, we applied interaction coherence analysis for Dark Web forums using the Hybrid Interaction Coherence (HIC) algorithm. Our algorithm utilizes both system features such as header information and quotations, and linguistic features such as direct address and lexical relation. Furthermore, several similarity-based methods, for example Vector Space Model, Dice equation, and sliding window, are used to address various types of noises. Two experiments have been conducted to compare our HIC algorithm with traditional linkage-based method, similarity-based method, and a simplified HIC method that does not address noise issues. The results demonstrate the effectiveness of our HIC algorithm for identifying interactions in Dark Web forums.