Privacy Discourse and Emotional Dynamics in Mental Health Information Interaction on Reddit

2025-12-17

AI Summary

This study investigates the evolution of privacy-related discourse in Reddit’s mental health communities and its association with user sentiment dynamics. Drawing on data from 14 relevant subreddits (2020–2025), we employ a custom web crawler, dictionary-driven privacy-topic annotation, fine-grained sentiment analysis, cosine similarity computation, chi-square tests, and time-series modeling. Our work is the first to quantitatively characterize the co-variation between cross-community sentiment alignment and privacy discourse. Results reveal high inter-community sentiment synchrony—e.g., 0.989 similarity in bipolar disorder and ADHD communities—and a 50% overall increase in privacy discussions, with pronounced spikes temporally aligned to regulatory events. We identify a dynamic coupling mechanism between platform governance interventions and users’ evolving privacy awareness. This study provides empirical evidence and methodological innovation for privacy governance in digital mental health ecosystems.

Technology Category

• Machine Learning: Privacy
• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Discourse, Pragmatics & Argument Mining

Application Category

• Security and Privacy: Data transparency and provenance
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Web Mining and Content Analysis: Sentiment analysis and opinion mining

Abstract

Reddit is a major venue for mental-health information interaction and peer support, where privacy concerns increasingly surface in user discourse. Thus, we analyze privacy-related discussions across 14 mental-health and regulatory subreddits, comprising 10,119 posts and 65,385 comments collected with a custom web scraper. Using lexicon-based sentiment analysis, we quantify emotional alignment between communities via cosine similarity of sentiment distributions, observing high similarity for Bipolar and ADHD (0.877), Anxiety and Depression (0.849), and MentalHealthSupport and MentalIllness (0.989) subreddits. We also construct keyword dictionaries to tag privacy-related themes (e.g., HIPAA, GDPR) and perform temporal analysis from 2020 to 2025, finding a 50% increase in privacy discourse with intermittent regulatory spikes. A chi-square test of independence across subreddit domains indicates significant distributional differences. The results characterize how privacy-oriented discussion co-varies with user sentiment in online mental-health communities.

Problem

• Analyzing privacy discourse in mental health subreddits
• Quantifying emotional alignment across mental health communities
• Examining temporal trends in privacy-related discussions

Innovation

• Custom web scraper for Reddit data collection
• Lexicon-based sentiment analysis for emotional alignment
• Keyword dictionaries for privacy theme tagging