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基于社交媒体的枪支所有权结构的开发和评估:计算推导和基准比较
Carole Roan Gresenz1, Lisa Singh2, Yanchen Wang3
1Department of Health Management and Policy, McCourt School of Public Policy, Georgetown University, Washington, DC, United States.
Journal of medical Internet research
|June 13, 2023
概括
社交媒体数据可以帮助追踪枪支所有权,补充传统调查. 机器学习模型对理解枪支暴力研究和相关行为有希望.
科学领域:
- 公共卫生 公共卫生
- 计算社会科学 计算社会科学
- 数据科学数据科学数据科学
背景情况:
- 枪支暴力研究在关键结构测量方面面临着严重的数据限制.
- 社交媒体提供了一个潜在的数据源来弥合这些差距.
- 开发方法来从社交媒体中获得与枪支相关的构造至关重要.
研究的目的:
- 利用社交媒体数据,开发一个机器学习模型,用于个人层面的枪支所有权.
- 评估来自社交媒体的州级枪支所有权结构的标准有效性.
主要方法:
- 将有关枪支所有权的调查答案与推特数据联系起来,以构建机器学习模型.
- 外部验证的模型使用精选的枪支相关推文.
- 从Twitter数据创建了州级所有权估计,并评估了与基准措施的标准有效性.
主要成果:
- 一个物流回归分类器实现了0.7的准确度和0.69的F1得分来预测枪支所有权.
- 在基于Twitter和基准州级所有权估计之间发现了强烈的正相关性 (Pearson r=0.63,Spearman r=0.64).
- 模型证明了国家一级枪支所有权的高标准有效性.
结论:
- 来自社交媒体数据的枪支所有权的机器学习模型显示了枪支暴力研究的巨大潜力.
- 社交媒体数据可以补充传统的数据来源,为枪支所有权的地理模式提供及时的见解.
- 需要进一步开发基于社交媒体的结构,以了解枪支行为,并为公共卫生战略提供信息.
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