Ali Shahmir H, Lowery Caitlin M, Trude Angela C B
Department of Social and Behavioral Sciences, New York University School of Global Public Health, New York, New York (Dr Ali); Department of Nutrition, University of North Carolina at Chapel Hill, North Carolina (Ms Lowery); and Department of Nutrition and Food Studies, New York University Steinhardt School of Culture, Education, and Human Development, New York, New York (Dr Trude).
J Public Health Manag Pract. 2023;29(6):E253-E262. doi: 10.1097/PHH.0000000000001804. Epub 2023 Jul 18.
Public reactions to health policies are vital to understand policy sustainability and impact but have been elusively difficult to dynamically measure. The 2021 launch of the Twitter Academic Application Programming Interface (API), allowing for historical tweet analyses, represents a potentially powerful tool for complex, comprehensive policy analyses.
Using the Philadelphia Beverage Tax (implemented January 2017) as a case study, this research extracted longitudinal and geographic changes in sentiments, and key influencers in policy-related conversations.
The Twitter API was used to retrieve all publicly available tweets related to the Tax between 2016 and 2019.
Twitter.
Users who posted publicly available tweets related to the Philadelphia Beverage Tax (PBT).
Tweet content, frequency, sentiment, and user-related information.
Tweet content, authors, engagement, and location were analyzed in parallel to key PBT events. Published emotional lexicons were used for sentiment analyses.
A total of 45 891 tweets were retrieved (1311 with geolocation data). Changes in the tweet volume and sentiment were strongly driven by Tax-related litigation. While anger and fear increased in the months prior to the policy's implementation, they progressively decreased after its implementation; trust displayed an inverse trend. The 50 tweeters with the highest positive engagement included media outlets (n = 24), displaying particularly high tweet volume/engagement, and public personalities (n = 10), displaying the greatest polarization in tweet sentiment. Most geo-located tweets, reflecting 321 unique locations, were from the Philadelphia region (55.2%). Sentiment and positive engagement varied, although concentrations of negative sentiments were observed in some Philadelphia suburbs.
Findings highlighted how longitudinal Twitter data can be leveraged to deconstruct specific, dynamic insights on public policy reactions and information dissemination to inform better policy implementation and evaluation (eg, anticipating catalysts for both heightened public interest and geographic, sentiment changes in policy conversations). This study provides policymakers a blueprint to conduct similar cost and time efficient yet dynamic and multifaceted health policy evaluations.
公众对卫生政策的反应对于理解政策的可持续性和影响至关重要，但一直难以动态衡量。2021年推出的推特学术应用程序编程接口（API），允许进行历史推文分析，这是一个用于复杂、全面政策分析的潜在强大工具。
以费城饮料税（2017年1月实施）为例，本研究提取了情绪的纵向和地理变化，以及政策相关对话中的关键影响因素。
使用推特API检索2016年至2019年期间与该税相关的所有公开可用推文。
推特。
发布与费城饮料税（PBT）相关公开可用推文的用户。
推文内容、频率、情绪和用户相关信息。
将推文内容、作者、参与度和位置与关键的费城饮料税事件并行分析。使用已发表的情感词典进行情感分析。
共检索到45891条推文（1311条带有地理位置数据）。推文数量和情绪的变化受到与税收相关诉讼的强烈驱动。虽然在政策实施前几个月愤怒和恐惧情绪增加，但在实施后逐渐减少；信任则呈现相反趋势。积极参与度最高的50位推特用户包括媒体机构（n = 24），其推文数量/参与度特别高，以及公众人物（n = 10），其推文情绪的两极分化最大。大多数带有地理位置的推文（反映321个独特地点）来自费城地区（55.2%）。情绪和积极参与度各不相同，尽管在费城的一些郊区观察到了负面情绪的集中。
研究结果突出了如何利用推特的纵向数据来解构关于公共政策反应和信息传播的具体、动态见解，以为更好的政策实施和评估提供信息（例如，预测引发公众高度关注以及政策对话中地理和情绪变化的催化剂）。本研究为政策制定者提供了一个蓝图，以进行类似的成本和时间高效但动态且多方面的卫生政策评估。
