This study collects 29 state-level public opinion policies,selecting 9 of them as the subjects for quantitative evaluation based on the PMC index model.Firstly,utilizing text mining technology and referring to relevant literature,an evaluation index system consisting of 9 primary indicators and 37 secondary indicators is constructed.Then,the PMC index scores of each policy are calculated,and PMC surface charts are plotted.Finally,the level of consistency,strengths,and weaknesses of the policies are analyzed.The results show that among the 9 policies,3 have reached a perfect level,and 6 are rated as excellent.This indicates that the overall quality of public opinion policies is good,with a high level of inter-nal consistency,but there is still room for further improvement.Therefore,it is recommen-ded that the policy-making departments design a dynamic policy development framework,establish a policy planning that combines long-term effects with short-term effectiveness,continuously improve policy content,and strengthen guidance on the integration of new technologies such as big data and artificial intelligence with practical work in policy content.
public opinion informationpolicy evaluationPMC index model
NETL
NSTL
万方数据
