Computational analyses identify addiction help-seeking behaviors on the social networking website Reddit: Insights into online social interactions and addiction support communities

The study addresses how people with substance use disorders (SUD) use Reddit to communicate about addiction and recovery, particularly in the context of COVID-19-related disruptions to in-person social connection. Given evidence that social connection predicts long-term recovery and that online forums may serve as proxies for support, the study aims to examine themes in Reddit posts related to addiction and recovery and assess how these themes align with existing research on digital platforms as support tools. The research questions are: RQ1: What themes emerge from a corpus of Reddit social media posts about addiction and recovery? RQ2: How do emergent themes triangulate ongoing research on the efficacy of digital platforms for substance use/abuse support?

Background literature indicates only 20% of U.S. individuals meeting DSM-5 criteria for SUD receive care, with relapse rates of 40–60% depending on substance and severity. Social support and recovery-oriented social networks are key predictors of long-term recovery. The COVID-19 pandemic increased substance use and overdoses and disrupted in-person social interactions, potentially shifting help-seeking toward online communities. Prior work shows online recovery forums (including Reddit) can be effective adjuncts to treatment across substances, but many studies have small samples or narrow inclusion criteria. Advances in NLP and SNA enable large-scale analysis of open-ended, diachronic social media data that can reveal content themes, psychosocial well-being, and social connections. The literature also notes potential harms of social media overuse (e.g., internalizing symptoms, perceived social comparison, sleep disruption) underscoring the need for balanced integration of digital tools in SUD support.

Data were collected from Reddit via its API, focusing on subreddits related to addiction and recovery active between January–August 2022. Inclusion required active forums with >1,000 subscribers. Subreddits analyzed: r/addiction, r/DecidingToBeBetter, r/SelfImprovement, r/OpiatesRecovery, r/StopSpeeding, r/RedditorsInRecovery, r/StopSmoking. After removing duplicates and non-English posts, the final sample comprised 9,066 posts. Preprocessing removed articles, prepositions, punctuation, abbreviations, numbers, and capitalization to enhance model clarity. Unsupervised NLP analyses used: TF-IDF to weight term importance; k-means clustering to identify thematic clusters (elbow plots suggested 2–3 clusters); PCA to reduce dimensionality for visualization (2D). Model fit was evaluated via k-fold cross-validated logistic regression, yielding 71% accuracy for a 2-cluster and 85% for a 3-cluster solution; subsequent analyses used the 3-cluster model. VADER sentiment analysis computed affect polarity scores per post. A macro searched posts for mentions of specific addictions to estimate frequency of substances discussed.

- Sample: 9,066 Reddit posts from seven addiction/recovery subreddits (Jan–Aug 2022). - Unsupervised analyses identified three clusters: (1) Personal addiction struggle/sharing recovery journey (n = 2,520); (2) Giving advice/counsel based on lived experience (n = 3,885); (3) Seeking advice/asking for support or advice (n = 2,661). - Sentiment (VADER): The 'Giving advice' cluster exhibited the highest affect; 'Personal addiction struggle' had the lowest affect. A one-way ANOVA comparing mean affect across clusters was significant, F(2, 5082) = 31.94, p < .001. Tukey’s post-hoc contrast indicated significant differences across most contrasts; the contrast between Asking for Advice and Sharing/Giving Advice was reported as not statistically significant (p = .026). - Substances discussed: Predominantly licit and illicit drugs (alcohol, tobacco, cocaine, heroin, etc.), with frequent mentions of pornography as a non-substance addiction, often co-occurring. Frequencies included: Marijuana (1,032), Heroin (978), Alcohol (802), Cocaine (419), Crack (176), Fentanyl (134), Pornography (115), Ecstasy (59). - Thematic content aligned with help-seeking, advice sharing (service), and personal storytelling consistent with recovery program practices.

The findings demonstrate that Reddit hosts robust discussions related to addiction and recovery, reflecting established recovery practices such as help-seeking, service (giving advice), and narrative sharing. The prevalence of 'asking for advice' and 'giving advice' supports the role of digital forums as sources of informational, emotional, and tangible support, paralleling in-person recovery networks. Themes emerged across diverse substances and co-occurring addictions, indicating broad applicability. The observed sentiment patterns suggest supportive tone in advice-giving and more negative affect in personal struggle narratives, consistent with recovery trajectories. Overall, results support that online forums can serve as effective proxies for social connection and adjuncts to treatment, particularly for individuals facing barriers to in-person care (stigma, cost, geography), while recognizing potential risks of overreliance on social media.

Reddit is used by individuals with SUD to disclose struggles, seek advice, and offer support, mirroring core elements of recovery communities. In a post-COVID-19 context of altered social communication, these online interactions may promote social connection and support recovery when in-person options are limited. The study contributes large-scale, data-driven evidence that digital platforms can aid recovery-related support. Future work should examine the effectiveness of these platforms more directly (e.g., longitudinal outcomes), employ supervised machine learning trained on human language for finer-grained topic detection, integrate ethical frameworks for digital interventions, and explore how online engagement translates to treatment linkage and sustained recovery.

- Authenticity: Anonymity of Reddit data limits verification of genuine SUD experiences. - Modeling: Reliance on unsupervised NLP (TF-IDF, k-means, PCA) may lead to misclassification; machines cannot fully match human judgment. - Sampling/qualitative depth: Only 50–75 posts per cluster were qualitatively reviewed; niche discussions likely remain uncharacterized. - Generalizability: Focus on specific subreddits/timeframe may not capture all addiction-related discourse on Reddit. - Future improvements: Recommend supervised machine learning trained on human language and more comprehensive qualitative analyses; ethical considerations are critical for classifier-based interventions.