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Front Pharmacol. 2018 Jul 26;9:791. doi: 10.3389/fphar.2018.00791. eCollection 2018.

Detection and Analysis of Drug Misuses. A Study Based on Social Media Messages.

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CNRS, Univ Lille, UMR 8163 STL-Savoirs Textes Langage, Lille, France.
Univ. Bordeaux, INSERM, Bordeaux Population Health Research Center, Team ERIAS, UMR 1219, Bordeaux, France.
DRUGS-SAFE National Platform of Pharmacoepidemiology, France.
CHU de Bordeaux, Pole de Sante Publique, Service D'information Medicale, Bordeaux, France.


Drug misuse may happen when patients do not follow the prescriptions and do actions which lead to potentially harmful situations, such as intakes of incorrect dosage (overuse or underuse) or drug use for indications different from those prescribed. Although such situations are dangerous, patients usually do not report the misuse of drugs to their physicians. Hence, other sources of information are necessary for studying these issues. We assume that online health fora can provide such information and propose to exploit them. The general purpose of our work is the automatic detection and classification of drug misuses by analysing user-generated data in French social media. To this end, we propose a multi-step method, the main steps of which are: (1) indexing of messages with extended vocabulary adapted to social media writing; (2) creation of typology of drug misuses; and (3) automatic classification of messages according to whether they contain drug misuses or not. We present the results obtained at different steps and discuss them. The proposed method permit to detect the misuses with up to 0.773 F-measure.


France; drug misuse; natural language processing; patient safety; social media

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