JMIR public health and surveillance
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JMIR Public Health Surveill · Oct 2016
"When 'Bad' is 'Good'": Identifying Personal Communication and Sentiment in Drug-Related Tweets.
To harness the full potential of social media for epidemiological surveillance of drug abuse trends, the field needs a greater level of automation in processing and analyzing social media content. ⋯ The study provides an example of the use of supervised machine learning methods to categorize cannabis- and synthetic cannabinoid-related tweets with fairly high accuracy. Use of these content analysis tools along with geographic identification capabilities developed by the eDrugTrends platform will provide powerful methods for tracking regional changes in user opinions related to cannabis and synthetic cannabinoids use over time and across different regions.