Getting high for likes: Exploring cannabis‐related content on TikTok

Abstract

Introduction With over 1 billion monthly users globally, a third of whom are under 14 years, TikTok's popularity is indisputable. Publicly available cannabis‐related content on this platform may influence perceptions of cannabis use. We aimed to examine how cannabis‐related videos are portrayed on TikTok. Methods Data were collected from TikTok using hashtag‐based keywords on cannabis‐related videos (n = 1377). Seven researchers documented video metrics (i.e. views, likes, comments) and independently coded videos for sentiment and theme. Results After removing duplicates and non‐related content, the final sample contained 881 videos. These videos had a median view count of 518 700 (SD = ±1 082 905), median likes count of 99 900 (SD = ±206 647) and median comment count of 931 (SD = ±2977). Many videos portrayed cannabis use positively (54.14%; collectively viewed 417 million times), with 15.84% of this subset actively depicting cannabis or administration products. The thematic analysis identified seven non‐mutually exclusive themes. Content portraying cannabis use as entertaining or humorous accounted for 71.74% of videos, with a further 42.90% discussing personal cannabis use experiences and 24.63% promoting the social and cultural acceptability of cannabis use. Discussion and Conclusions Our sample revealed over half of videos portrayed cannabis use positively and none were age restricted. All were publicly accessible through standard web and smartphone applications. With previous research demonstrating that exposure to cannabis‐related content can influence adolescents' attitudes and problematic cannabis use, it is important more effective age restrictions and regulations are introduced to social media platforms.

#TurntTrending: a systematic review of substance use portrayals on social media platforms

“…A total of 15 905 182 substance‐related social media posts (15 804 353 text posts, 68 023 image posts, and 32 470 video posts) were assessed across all 73 studies. Twitter data was analysed in 34 studies [20–53]; 23 studies examined YouTube [54–76]; 10 assessed Instagram content [77–85]; 4 studies used Pinterest images [85–88]; TikTok videos were analysed in 2 studies [89, 90]; and Weibo content was assessed in a single study [91]. E‐cigarettes were the most common category analysed ( n = 24 studies), followed by tobacco ( n = 20 studies), cannabis ( n = 18 studies), opiates ( n = 6 studies), alcohol ( n = 4 studies), psychostimulants ( n = 1 study), stimulants/amphetamines ( n = 1 study), inhalants ( n = 1 study), novel psychoactive substances (NPS) ( n = 1 study) and polysubstance use ( n = 1 study).…”

Emerging Adults’ Exposure to and Postings About Substance Use on Social Media: An Observational Study

“…Compared to text content, visual content may be more engaging (Strowger & Braitman, 2022) and provide more key contextual information. Most substance use posts are in a positive context (Beullens & Schepers, 2013; Erevik et al, 2018; Rutherford et al, 2022), and users may see a social event in which others are enjoying themselves and each other as they consume alcohol, which in turn may increase perceived approval of and subsequent use (Nesi et al, 2017). These visual portrayals may be especially important for emerging adults as they navigate new social contexts and determine how certain behaviors are perceived.…”

“…Emerging adults can utilize social media to gain an understanding of how substances are valued, viewed, and used among new peers. Substances are often portrayed favorably on social media (Beullens & Schepers, 2013; Erevik et al, 2018; Rutherford et al, 2022) and receive more likes compared to non-substance use posts, signaling social approval (Kurten et al, 2022). It is therefore critical to understand how emerging adults are exposed to others’ social media substance postings, as this exposure may play a key role in emerging adults’ own substance use.…”

Content Analysis of Nicotine Poisoning (Nic Sick) Videos on TikTok: Retrospective Observational Infodemiology Study

“…The videos were manually annotated (using binary classification—whether the video depicted nicotine poisoning or nicotine sickness or not) and then inductively coded for specific themes that emerged, such as showing active vaping, specific adverse events, or nicotine sickness experiences ( Table 1 ). Furthermore, based on prior research studies [ 7 , 32 , 33 ] that have conducted content analysis on TikTok videos, we also coded the following metrics and associated metadata: (1) user engagement (views, likes, comments, shares, followers, verification); (2) video characteristics (duration, caption, text on screen, subtitles, music); and (3) video type (original, duet, stitch). An original video is a microvideo uploaded by a TikTok user and is the primary source of user-generated posts on the platform.…”