The Dark Web hosts a variety of Q&A forums that facilitate discussions on topics ranging from technical guidance to illicit activities. This study investigates the linguistic and structural characteristics of three prominent Dark Web Q&A forum onion services—Onion1 (Deepweb Questions and Answers), Onion2 (Deep Answers), and Onion3 (Repostas Ocultas)—using a combination of topic modeling and quantitative text analysis. We employ Sklearn (TF-IDF) and Gensim (LDA) to extract and compare dominant topics, alongside metrics of lexical diversity, semantic diversity and syntactic complexity. Our findings reveal significant differences in topic diversity and linguistic patterns across the forums, with Onion1 exhibiting a focus on technical and financial discussions, Onion2 emphasizing community-driven and security-related topics, and Onion3 showing a narrower thematic scope influenced by its structured Q&A format and language-specific content. Statistical analyses, including Kruskal-Wallis tests and Dunn’s post-hoc comparisons, confirm these differences, highlighting the distinct communicative norms and user behaviors of each forum. The results underscore the importance of considering forum-specific characteristics when analyzing Dark Web communities and provide insights into the thematic and linguistic diversity of these platforms.