哪些社交媒体平台能为监测阿片类药物危机提供最翔实的数据?

Kristy A Carpenter, Anna T Nguyen, Delaney A Smith, Issah A Samori, Keith Humphreys, Anna Lembke, Mathew V Kiang, Johannes C Eichstaedt, Russ B Altman
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引用次数: 0

摘要

背景和目的社交媒体可以让人们实时了解药物使用、成瘾和康复的趋势。之前的研究已经利用了 Reddit 和 X(前 Twitter)等平台的数据,但有关数据访问的政策不断变化,威胁到了这些平台在阿片类药物过量监测系统中的可用性。在此,我们评估了一系列平台在检测阿片类药物危机新趋势方面的潜力。设计我们确定了 72 个在线平台,这些平台拥有大量的全球用户群,或曾在阿片类药物相关研究中被引用过。我们评估了每个平台是否符合我们对社交媒体的定义、北美用户群的规模以及阿片类药物相关讨论的数量。我们列出了一份由 11 个符合标准的平台组成的短名单。我们记录了入围平台的基本特征、阿片类药物讨论的数量和性质、监管药物相关讨论的官方政策以及数据的可访问性。设置美国和加拿大。衡量标准我们通过特定平台上阿片类术语的谷歌搜索点击量来量化阿片类讨论的数量。我们通过使用大型语言模型生成的俚语来捕捉非正式语言。我们报告了与阿片类药物相关的点击量以及与阿片类药物相关的点击量占普通名词点击量的比例。研究结果我们发现,TikTok、YouTube 和 Facebook 最有可能用于阿片类药物相关监控。TikTok 和 Facebook 上与毒品有关的讨论相对数量最多。TikTok 上的语言主要是非正式的。许多平台都为研究提供了数据访问工具,但不断变化的公司政策和用户规范造成了不稳定性。不同平台的用户人口构成差异很大。结论社交媒体数据源为检测阿片类药物使用趋势带来了希望,但研究人员必须考虑每个平台数据的实用性、可访问性和稳定性。可能需要采取将多个平台混合使用的策略,以覆盖受疫情影响的所有人群。
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Which Social Media Platforms Provide the Most Informative Data for Monitoring the Opioid Crisis?
Background and Aims Social media can provide real-time insight into trends in substance use, addiction, and recovery. Prior studies have leveraged data from platforms such as Reddit and X (formerly Twitter), but evolving policies around data access have threatened their usability in opioid overdose surveillance systems. Here, we evaluate the potential of a broad set of platforms to detect emerging trends in the opioid crisis. Design We identified 72 online platforms with a substantial global user base or prior citations in opioid-related research. We evaluated each platform's fit with our definition of social media, size of North American user base, and volume of opioid-related discourse. We created a shortlist of 11 platforms that met our criteria. We documented basic characteristics, volume and nature of opioid discussion, official policies regulating drug-related discussion, and data accessibility of shortlisted platforms. Setting USA and Canada. Measurements We quantified the volume of opioid discussion by number of platform-specific Google search hits for opioid terms. We captured informal language by including slang generated using a large language model. We report the number of opioid-related hits and proportion of opioid-related hits to hits for common nouns. Findings We found that TikTok, YouTube, and Facebook have the most potential for use in opioid-related surveillance. TikTok and Facebook have the highest relative amount of drug-related discussions. Language on TikTok was predominantly informal. Many platforms offer data access tools for research, but changing company policies and user norms create instability. The demographics of users varies substantially across platforms. Conclusions Social media data sources hold promise for detecting trends in opioid use, but researchers must consider the utility, accessibility, and stability of data on each platform. A strategy mixing several platforms may be required to cover all demographics suffering in the epidemic.
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