Evaluating Mental Health Discourse in Black Online Communities: An Exploratory Analysis Using Topic Modeling and Emotion Recognition

Background and Purpose

Online communities, particularly platforms like Reddit, serve as essential spaces for marginalized groups to share experiences, seek support, and engage in discussions about mental health and social inequities. For Black individuals, these platforms provide an avenue to navigate systemic barriers and express their emotional experiences. Despite the significance of these discussions, there has been limited research analyzing the themes and emotional dimensions of these interactions to better understand how they relate to broader mental health challenges and societal inequities. The objectives for this study are as follows:

1. Identify key themes in a corpus of Reddit posts from popular spaces for Black individuals, including r/Blackladies and r/Blackfellas, and explore how emergent themes relate to health and well-being.
2. Analyze the emotional tone of posts using emotion recognition.
3. Compare emergent topics and emotion spectrums between the subreddits.

This study applies natural language processing and social media mining to analyze archived Reddit posts from two of the most popular culturally specific forums, conducting an exploratory analysis of related themes and topics.

Methods

We conducted a thorough collection of archived posts from r/Blackladies and r/Blackfellas, employing preprocessing techniques such as stopword removal, lemmatization, and artifact cleaning. A neural network topic modeling pipeline known as BERTopic was utilized to uncover emergent themes, while emotion recognition was carried out using the Roberta-base_go-emotions model. Findings are derived from a dataset of 12,919 (r/Blackladies) and 9,318 (r/Blackfellas) after excluding posts with missing data (i.e., deleted). Future research will expand this analysis to include human-coding of a randomly selected subset of posts from the two samples to evaluate model performance.

Results

Topic modeling results highlighted significant themes encompassing identity, relationships, pop culture, and health-related discussions between the groups. Among posts from r/Blackladies, we found curiosity, disappointment (7.02%), annoyance (6.30%), gratitude (6%), and confusion (4.70%) to be among the most prominent emotions identified by the model. Notably, findings among r/Blackfellas revealed a rich affective spectrum with sadness accounting for 16% of posts, followed by curiosity (7%), annoyance (2%), and gratitude (2%).

Conclusions and Implications

This study marks a foundational step in utilizing AI-driven methodologies to yield nuanced insights into health concerns faced by marginalized populations. The research not only fosters a deeper understanding of the experiences shared on online platforms but also emphasizes the potential for AI to guide equitable mental health interventions. Additionally, this project highlights the need to tackle algorithmic challenges to ensure fair and accurate analyses.