运用社交媒体数据评估公共政策满意度：方法构建与基于“双减”政策的应用
Using Social Media Data to Evaluate Policy Satisfaction: Methodology Construction and Application of “Double Reduction” Policies

大数据时代构建一套运用社交媒体数据评估公共政策满意度的方法具有重要意义。文章从社交媒体数据与政策评估融合的角度，提出了运用社交媒体数据评估公共政策满意度的逻辑、维度与相应的方法和技术。其逻辑在于明确社交媒体数据和政策评估的共同性、互补性的基础上将社交媒体的优势、方法、技术与政策评估相整合，整合的维度包括政策后果话题识别、政策后果关注度、政策满意度、政策满意度影响因素四个方面，文本聚类、话题热度分析、情绪分析、基于情感极性的主题建模等有助于相关评估维度的实现。对C省份“双减”政策实施公众满意度评估的实践表明，该方法具有较强的优势和可行性。文章对大数据时代公共政策评估的创新进行了探索，并为“双减”政策实施的优化提供了一定启示。
In the era of big data, it is of great significance to construct a set of methods for evaluating policy satisfaction using social media data. From the perspective of the integration of social media data and policy evaluation, this paper puts forward the logic, dimension and corresponding methods of using social media data to evaluate public policy satisfaction. Its logic is to integrate the advantages, methods and technologies of social media with policy evaluation on the basis of clarifying the commonality and complementarity of social media data and policy evaluation. The integration dimension includes four aspects: topic identification of policy consequences, attention to policy consequences, policy satisfaction and influencing factors of policy satisfaction. Text clustering, topic heat analysis, sentiment analysis and topic modeling based on emotion polarity are helpful to the realization of relevant evaluation dimensions. The practice of public satisfaction evaluation on the implementation of “double reduction” policy in C province shows that this method has strong advantages and feasibility. This paper explores the innovation of policy evaluation in the era of big data, and provides some enlightenment for the optimization of the implementation of “double reduction” policy.