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Signs & symptoms of Dextromethorphan exposure from YouTube.

Michael Chary, Emily H Park, Andrew McKenzie, Julia Sun, Alex F. Manini, Nicholas Genes

PLoS One February 12, 2014 DOI: 10.1371/journal.pone.0082452 (opens in new tab)

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AI-extracted from the abstract
Characteristics Computational linguistics study of social media comments Peer reviewed
Population YouTube commenters discussing dextromethorphan use
Keywords Humans Substance-related disorders Dextromethorphan Cluster analysis Linguistics Internet Pattern recognition, automated Social media Symptom assessment Illicit drugs
Key points Argues that YouTube comments, analyzed with computational linguistics, can recreate many clinically described signs and symptoms of dextromethorphan ingestion at various doses, and that social networks can enhance understanding of recreational drug effects.

Abstract

Detailed data on the recreational use of drugs are difficult to obtain through traditional means, especially for substances like Dextromethorphan (DXM) which are available over-the-counter for medicinal purposes. In this study, we show that information provided by commenters on YouTube is useful for uncovering the toxicologic effects of DXM. Using methods of computational linguistics, we were able to recreate many of the clinically described signs and symptoms of DXM ingestion at various doses, using information extracted from YouTube comments. Our study shows how social networks can enhance our understanding of recreational drug effects.

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