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

机译:药物滥用的检测和分析。基于社交媒体消息的研究

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摘要

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.
机译:当患者不遵循处方而采取可能导致潜在危害情况的措施时,可能会发生药物滥用,例如摄入错误剂量(过度使用或使用不足)或出于与指示不同的适应症而使用药物。尽管这种情况很危险,但患者通常不会向医生报告滥用药物的情况。因此,研究这些问题还需要其他信息来源。我们假设在线健康论坛可以提供此类信息,并建议加以利用。我们工作的总体目的是通过分析法国社交媒体中用户生成的数据来自动检测滥用药物并进行分类。为此,我们提出了一种多步骤方法,其主要步骤是:(1)索引具有扩展词汇量的消息,以适应社交媒体写作; (2)建立药物滥用类型学; (3)根据消息是否包含滥用毒品对消息进行自动分类。我们介绍了在不同步骤获得的结果并进行了讨论。所提出的方法可以检测出高达0.773 F值的误用。

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