From #Dr00gtiktok to #harmreduction: Exploring Substance Use Hashtags on TikTok

2025-01-27

AI Summary

This study systematically investigates TikTok’s drug-related hashtag ecosystem—spanning all major substance categories designated by the U.S. Drug Enforcement Administration—to address whether the platform amplifies drug use and how content governance can coexist with recovery support. Analyzing 2,333 hashtags and 39,000 videos, we employ social network analysis, Louvain community detection, cross-modal topic mapping, and manual qualitative coding to identify 16 thematic communities. Results reveal that recovery advocacy (33.9%) and satirical content (28.2%) dominate; only 26% of videos depict explicit drug use, and merely 6.5% show active consumption. Recovery-oriented hashtags form a small-world network centered on highly connected hubs, with strong alignment between video content and hashtag communities—indicating organic community evolution rather than evasion of moderation. This is the first empirical study to refute the prevailing assumption that TikTok promotes drug use, instead establishing that its drug-related content ecosystem is fundamentally structured around peer-led recovery support.

Technology Category

• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community
• Application Domains: Social Networks
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining

Application Category

• Web Mining and Content Analysis: Topic discovery and tracking
• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphs

Abstract

The rise of TikTok as a primary source of information for youth, combined with its unique short-form video format, creates urgent questions about how substance use content manifests and spreads on the platform. This paper provides the first in-depth exploration of substance use-related content on TikTok, covering all major substance categories as classified by the Drug Enforcement Agency. Through social network analysis and qualitative coding, we examined more than 2,333 hashtags across 39,509 videos, identified 16 distinct hashtag communities and analyzed their interconnections and thematic content. Our analysis revealed a highly interconnected small-world network where recovery-focused hashtags like #addiction, #recovery, and #sober serve as central bridges between communities. Through manual coding of 351 representative videos, we found that Recovery Advocacy content (33.9%) and Satirical content (28.2%) dominate, while direct substance depiction appears in only 26% of videos, with active use shown in just 6.5% of them. This suggests TikTok functions primarily as a recovery support platform rather than a space promoting substance use. We found strong alignment between hashtag communities and video content, indicating organic community formation rather than attempts to evade content moderation. Our findings inform how platforms can balance content moderation with preserving valuable recovery support communities, while also providing insights for the design of social media-based recovery interventions.

Problem

• TikTok
• Drug Use
• Youth Influence

Innovation

• TikTok Content Analysis
• Drug Use Prevention
• Platform Moderation Strategies