在互联网搜索引擎中使用搜索量预测日本县级福利指标:传染病学研究
1Course of Advanced Nursing Sciences, Human Health Sciences, Faculty of Medicine, Kyoto University, Kyoto, Japan.
Journal of medical Internet research
|November 11, 2024
概括
这项研究表明,互联网搜索数据可以准确地预测日本的区域福祉. 这为决策者提供了一种快速,具有成本效益的方法来评估公共福祉.
科学领域:
- 社会科学 社会科学 社会科学
- 数据科学数据科学数据科学
- 公共政策 公共政策
背景情况:
- 像GDP这样的传统经济指标不足以评估多方面的福祉.
- 现有的福利指标面临诸如高调查成本和有限的区域评估能力等挑战.
- 网络日志数据为评估幸福感提供了一个有希望,具有成本效益和及时的替代方案.
研究的目的:
- 利用互联网搜索数据,开发日本地区福祉指标的预测模型.
- 为决策者提供一个可访问和具有成本效益的工具,用于评估县级公共福利.
主要方法:
- 利用日本的区域福祉指数 (RWI) 作为47个县 (2010-2019) 的结果变量.
- 作为预测变量,使用了相关关键字的谷歌趋势相对搜索量 (RSV) 数据.
- 应用弹性网方法,通过交叉验证优化,使用RSV预测RWI,用RMSE和R2评估准确性.
主要成果:
- 从谷歌趋势数据中确定了211个相关的关键词.
- 最佳弹性网模型 (α=0.1, λ=0.906) 在训练数据 (R2=0.904) 上实现了高预测准确度.
- 该模型在2019年测试数据上表现良好 (R2=0.665),表明其预测能力.
结论:
- 通过Elastic Net分析的互联网搜索日志数据,有效地预测了日本的县区福祉.
- 这种方法为传统的幸福调查提供了快速和经济高效的替代方案.
- 该方法为基于证据的政策制定提供了有价值的数据,以提高社会福祉.
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