[分析社交媒体上与过量服用相关的帖子]
Ryuya Sato1, Masami Tsuchiya1, Rintaro Ichiyama1
1Division of Drug Informatics, Keio University Faculty of Pharmacy.
Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
|December 1, 2024
概括
社交媒体分析揭示了故意药物过量 (OD) 的趋势. 在帖子中经常提到非处方药和处方药,午夜高峰表明与OD事件的情感联系.
科学领域:
- 药理学 药理学是指药理学的学科.
- 社会科学 社会科学 社会科学
- 计算语言学 计算语言学
背景情况:
- 蓄意的药物过量 (OD) 是一个全球性的社会问题.
- 有限的研究已经探索了社交媒体数据,以了解药物滥用模式.
- 社交网络服务为分析OD趋势提供了一种新的途径.
研究的目的:
- 分析Twitter (X) 帖子的药物过量 (OD) 特性和趋势.
- 评估社交媒体数据和自然语言处理 (NLP) 对OD研究的有用性.
- 为了识别常常被滥用的非处方药和处方药.
主要方法:
- 在2023年1月10日至2月8日期间从Twitter (X) 收集了30203个含有"OD"的日本帖子.
- 使用精心调整的BERT模型来对OD相关职位进行分类.
- 分析分类帖子的毒品类型,情感背景和发布时间.
主要成果:
- 大约三分之一的"描述ODing的帖子" (5,283个帖子) 提到了特定的药物.
- 通常引用的OTC药物包括可代因,德克斯特罗梅索芬,以弗德林和二胺.
- 常常提到的处方药物,如二类药物和普雷加巴林;帖子在午夜左右达到顶峰.
结论:
- 推特 (X) 分析为药物滥用模式和情绪背景提供了宝贵的见解.
- 社交媒体监控可以帮助识别有风险的个人,并为OD预防策略提供信息.
- 提高公众意识和加强社交媒体监控对于减轻滥用药物风险至关重要.
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