ArticleJMIR formative research2022
Identifying Health-Related Discussions of Cannabis Use on Twitter by Using a Medical Dictionary: Content Analysis of Tweets.
Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Transformer-Based Topic Modeling: Characterizing Cannabis Product Adverse Experiences Self-Reported as Requiring Medical Attention on Reddit.Journal of medical Internet research · 2026Article
- Examining the Popularity, Content, and Intersections With the Substance Abuse and Mental Health Services Administration's Definition of Recovery in a Nonclinical Online Cannabis Cessation Community: Infodemiology Study of Reddit Posts.Journal of medical Internet research · 2024Article
- Twitter activity surrounding the Finnish green party's cannabis legalisation proposal: A mixed-methods analysis.Nordisk alkohol- & narkotikatidskrift : NAT · 2023Article
- Using Social Media Data to Investigate Public Perceptions of Cannabis as a Medicine: Narrative Review.Journal of medical Internet research · 2023Review
- Social media discourse and internet search queries on cannabis as a medicine: A systematic scoping review.PloS one · 2023Article
- Consumer-Generated Discourse on Cannabis as a Medicine: Scoping Review of Techniques.Journal of medical Internet research · 2022Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe cannabis product and regulatory landscape is changing in the United States. Against the backdrop of these changes, there have been increasing reports on health-related motives for cannabis use and adverse events from its use. The use of social media data in monitoring cannabis-related health conversations may be useful to state- and federal-level regulatory agencies as they grapple with identifying cannabis safety signals in a comprehensive and scalable fashion.
objectiveThis study attempted to determine the extent to which a medical dictionary-the Unified Medical Language System Consumer Health Vocabulary-could identify cannabis-related motivations for use and health consequences of cannabis use based on Twitter posts in 2020.
methodsTwitter posts containing cannabis-related terms were obtained from January 1 to August 31, 2020. Each post from the sample (N=353,353) was classified into at least 1 of 17 a priori categories of common health-related topics by using a rule-based classifier. Each category was defined by the terms in the medical dictionary. A subsample of posts (n=1092) was then manually annotated to help validate the rule-based classifier and determine if each post pertained to health-related motivations for cannabis use, perceived adverse health effects from its use, or neither.
resultsThe validation process indicated that the medical dictionary could identify health-related conversations in 31.2% (341/1092) of posts. Specifically, 20.4% (223/1092) of posts were accurately identified as posts related to a health-related motivation for cannabis use, while 10.8% (118/1092) of posts were accurately identified as posts related to a health-related consequence from cannabis use. The health-related conversations about cannabis use included those about issues with the respiratory system, stress to the immune system, and gastrointestinal issues, among others.
conclusionsThe mining of social media data may prove helpful in improving the surveillance of cannabis products and their adverse health effects. However, future research needs to develop and validate a dictionary and codebook that capture cannabis use-specific health conversations on Twitter.
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