Using data mining to improve the efficiency of government governance in the context of carbon neutrality is an important way to achieve the modernization of the national governance system. This study starts with the logic of carbon neutral issues, analyzes the factors and indicators that affect the effectiveness of social governance, and constructs the evaluation index system of government social governance efficiency based on data mining application under the background of carbon neutral, including per capita GDP, per capita domestic power consumption of residents, per capita CO2 emissions, per capita green area, industrial waste gas treatment rate, industrial wastewater discharge compliance rate and other indicators, which includes 4 first-class indicators, 19 second-class indicators and 38 third class indicators. Then, the CV-CRITICAL (coefficient of variation critical) index weight determination algorithm is used to determine the index weight. The Pearson correlation coefficient method is used to evaluate the correlation between the two vectors, and then the rationality of the government social governance efficiency evaluation index system based on data mining applications is evaluated. The evaluation results show that the level of social governance effectiveness of the Chinese government is on the rise from 2016 to 2021. This study promotes the application of improving the efficiency of government social governance in the context of carbon neutrality, and provides tools for relevant assessment through data mining technology. This research can not only deepen the theoretical connotation of government governance effectiveness, but also help promote the application of big data in government governance practice.