Penn State Departments of Political Science and African American Studies, 308 Pond Laboratory, University Park, PA, 16802, USA.
Penn State Department of Political Science and the Center for Social Data Analytics, Pond Laboratory, University Park, PA, 16802, USA.
Soc Sci Med. 2022 Jul;305:115091. doi: 10.1016/j.socscimed.2022.115091. Epub 2022 Jun 2.
Risk assessment and response is important for understanding human behavior. The divisive context surrounding the coronavirus pandemic inspires our exploration of risk perceptions and the polarization of mitigation practices (i.e., the degree to which the behaviors of people on the political "Left" diverge from those on the "Right"). Specifically, we investigate the extent to which the political polarization of willingness to comply with mitigation behaviors changes with risk perceptions.
Analyses use data from two sources: an original dataset of Twitter posts and a nationally-representative survey. In the Twitter data, negative binomial regression models are used to predict mitigation intent measured using tweet counts. In the survey data, logit models predict self-reported mitigation behavior (vaccination, masking, and social distancing).
Findings converged across both datasets, supporting the idea that the links between political orientation and willingness to follow mitigation guidelines depend on perceived risk. People on the Left are more inclined than their Right-oriented colleagues to follow guidelines, but this polarization tends to decrease as the perceived risk of COVID-19 intensifies. Additionally, we find evidence that exposure to COVID-19 infections sends ambiguous signals about the risk of the virus while COVID-19 related deaths have a more consistent impact on mitigation behaviors.
Pandemic-related risks can create opportunities for perceived "common ground," between the political "Right" and "Left." Risk perceptions and politics interact in their links to intended COVID-19 mitigation behavior (as measured both on Twitter and in a national survey). Our results invite a more complex interpretation of political polarization than those stemming from simplistic analyses of partisanship and ideology.
风险评估和应对对于理解人类行为很重要。围绕冠状病毒大流行的分裂性背景激发了我们对风险认知和缓解措施（即政治“左”派和“右”派的行为差异程度）的极化的探索。具体而言，我们调查了随着风险认知的变化，人们对遵守缓解行为的政治两极分化程度的变化。
分析使用了两个来源的数据：原始的 Twitter 帖子数据集和全国代表性调查。在 Twitter 数据中，使用负二项回归模型预测用推文数量衡量的缓解意愿。在调查数据中，对数模型预测自我报告的缓解行为（接种疫苗、戴口罩和保持社交距离）。
两个数据集的结果都趋同，支持了这样一种观点，即政治倾向与遵守缓解指南的意愿之间的联系取决于感知风险。与右翼人士相比，左翼人士更倾向于遵循指导方针，但这种两极分化趋势随着对 COVID-19 的风险感知加剧而减弱。此外，我们还发现，接触 COVID-19 感染会对病毒的风险发出模糊的信号，而与 COVID-19 相关的死亡对缓解行为的影响则更为一致。
与大流行相关的风险可以为政治“右”派和“左”派之间创造出感知的“共同点”。风险认知和政治在与预期的 COVID-19 缓解行为的联系中相互作用（在 Twitter 和全国性调查中都有衡量）。我们的结果邀请对政治两极分化进行比那些基于党派和意识形态的简单分析更为复杂的解释。
