Hidradenitis suppurativa on Reddit: Natural language processing for thematic analysis

ABSTRACT

Background: Patients with hidradenitis suppurativa (HS) face high psychosocial burden and difficulty in managing their chronic disease. Online support groups and forums are important spaces for patients to share emotional support and management strategies. Objective: To analyze patient-generated online forum posts in Reddit in order to uncover significant HS-related patient concerns and identify HS topics of particular interest to patients. Methods: We collected posts made in the subreddit forum “/r/hidradenitis” between July 1, 2016 to June 30, 2021. Latent derelict allocation (LDA), an unsupervised machine learning model, was applied to split the posts into topics. Keywords for each topic supplied by LDA were used to manually assign topic labels. Results: 61,627 posts by 6948 unique users met inclusion criteria. After applying LDA to the posts, 28 significant topics of conversation emerged that could be organized into 4 major themes management (56.7%), mental health (20.6%), clinical presentation (13.1%), and logistics (7.6%). The top four topics were support (10.0%), diet (9.5%), wound care (7.3%) and intimate relationships (6.2%). Contemporary topics of interest included biologics (3.5%), COVID-19 (1.2%), and cannabis (1.1%). Limitations: LDA classifies posts into topics based on frequencies of words within the posts without an understanding of the language or context. Conclusions: This LDA-based analysis demonstrated a wide breadth of discussion occurring in an online forum, Reddit, with strong participation. Awareness of popular topics within the HS community can help providers engage with patients and encourage researchers to investigate understudied HS topics that are important to patients.