Table 7_How online public opinion evolves before and after policy adjustments in response to major public health emergencies.xlsx

BackgroundIn recent years, incidents of public opinion triggered by major public health emergencies have emerged endlessly. Existing studies have focused on public attitudes during the early stages of containment measures but lacked research on how public opinion evolves after those measures are relaxed. In late 2022, however, China optimized its COVID-19 control measures, providing a unique window for this study.
ObjectiveTo reveal public attitudes toward the adjustment of response measures for major public health emergencies and how these attitudes evolve over time, and to provide a reference for improving related policies and managing public opinion.
MethodsWe collected Baidu Index and Weibo post data related to “epidemic prevention and control” between October 11, 2022 and March 15, 2023. Guided by the “Public Opinion Life Cycle Theory,” we analyzed the evolution of public opinion intensity using the Baidu Index. We applied the SKEP model for sentiment analysis on Weibo posts, exploring changes in public sentiment and differences among groups. Additionally, we used the LDA model for topic mining on Weibo posts, examining the evolution of discussion topics and their underlying causes.
ResultsDuring the early stages of adjustments to prevention and control measures, public opinion surged but quickly subsided to a level significantly lower than before, following the announcement of more targeted measures. In the long term, the public generally holds a positive attitude toward these adjustments, though negative sentiment may emerge in the short term. Prior to the adjustments, discussions focused on community prevention and control. In the early phase, debates were intense, with expectations for a return to normal life and economic recovery alongside concerns about health risks and medical resources. After a prolonged adjustment period, discussions on economic and daily-life topics increased, but concerns about medication and reinfection risks remained high.
ConclusionTo guide the healthy development of public opinion, policymakers should clearly explain the rationale for policy adjustments, promptly address public concerns, and encourage enterprises and opinion leaders to share positive information; additionally, they should ensure sufficient medical resources are secured before implementing policy changes and roll them out in a well-organized, step-by-step manner.

研究背景
近年来，重大公共卫生事件引发的舆情事件层出不穷。现有研究多聚焦于防控措施实施初期的公众态度，却鲜有针对防控措施优化放松后舆情演化路径的相关探讨。2022年末我国优化调整新冠疫情防控政策，为本研究提供了独特的观测窗口。

研究目标
揭示公众对重大公共卫生事件应急响应措施调整的态度及其随时间的演化规律，为完善相关政策、优化舆情管理提供参考依据。

研究方法
本研究采集了2022年10月11日至2023年3月15日期间与“疫情防控”相关的百度指数（Baidu Index）及微博博文数据。本研究以舆情生命周期理论（Public Opinion Life Cycle Theory）为指导，依托百度指数分析舆情热度的演化趋势；针对微博博文，采用SKEP模型开展情感分析，探究公众情感的动态变化与群体差异。此外，借助潜在狄利克雷分配（LDA）模型对微博博文进行主题挖掘，剖析讨论主题的演化路径及其深层动因。

研究结果
防控措施优化调整初期，舆情热度出现大幅攀升，但在更具针对性的措施公布后迅速回落至显著低于调整前的水平。长期来看，公众对防控政策调整整体持积极态度，但短期内或出现负面情绪。政策调整前，公众讨论的核心主题为社区防控；调整初期，讨论争议激烈，公众既期待回归正常生活、推动经济复苏，同时也担忧健康风险与医疗资源储备。经过较长一段时间的政策调整后，公众对经济与日常生活相关话题的讨论有所增加，但对用药需求与再感染风险的担忧仍居高不下。

研究结论
为引导舆情健康发展，政策制定者应清晰阐释政策调整的逻辑依据，及时回应公众关切，并鼓励企业与意见领袖分享积极信息；此外，在推出政策调整前，需保障充足的医疗资源储备，并以有序、分步的方式推进政策落地。