‘I just need to vent’ : A Text Mining Study Analysing Reddit Discourse on Obsessive-Compulsive-Disorder on r/OCD using BERT-based models

Obsessive-compulsive disorder is a highly prevalent mental health condition, characterized by persistent and distressing obsessions and compulsions, causing significant impairment in daily functioning. Yet, research on the lived experience of individuals with OCD remains limited. As people increasingly seek out anonymous online spaces such as Reddit to discuss their experiences with OCD, these firsthand accounts present a novel opportunity for insight. This study leveraged transformer-based BERT models (BERTopic, roBERTa-base-sentiment, roBERTa-base-emotion) to conduct topic modelling, sentiment analysis and emotion recognition on 5,083 Hot posts from the r/OCD subreddit that were scraped between February and April 2025. Topic modelling identified both well-established and lesser researched aspects of OCD across 34 topics. Most topics represented known obsessions and compulsions that could be attributed to well-known OCD dimensions. Other topics discussed general OCD concepts, treatment, social impact, and substance use. Moreover, analysis captured understudied aspects of OCD, namely its intersections with pregnancy, social media and family. Majority were overwhelmingly negative in sentiment with fear and sadness as the most prominent emotions, underscoring the distressing nature of OCD. These findings demonstrate that transformer-based text mining can validate clinical knowledge and capture novel insight, offering a scalable, low-preprocessing method to analyse Reddit data for clinical insight.