Data-driven network analysis methods provide new perspectives for the understand-ing of emission reduction synergy.This paper sorts out the historical logic,spatial characteristics and driving factors of China-style modernization regional emission reduction policy synergy from both historical and practical perspectives,in order to provide reference for policy formulation.Dif-ferent from the existing investigation of the synergy between government departments,this paper constructs an inter-provincial policy network measurement model based on natural language process-ing,based on big data text analysis to measure the coordination degree of 4988 inter-provincial and regional policies and 275 central policy concerns,introduces social network analysis technology to construct an inter-provincial policy coordination network,and studies the impact of central policy fo-cus on local emission reduction policy coordination.Based on the BERTopic model,it is found that the regional coordinated emission reduction policy has gone through three stages:radiation in key demonstration areas,regional coordinated strategic guidance and national systematic classification policy,and three mechanisms have been formed:differentiated target response,expanded synergy scope and concrete policy content.Applied social network analysis shows that there are 457 emission reduction synergies coexisting among 31 provinces,and the network shows a tight imbalance be-tween the central and eastern parts and the loose imbalance in the western and northern parts of the south.Among them,Beijing,Shanghai and Jiangsu are the core actors,Jilin,Ningxia and Hei-longjiang are the marginal actors,and Hubei and Hunan play the role of"bridges";Finally,based on the secondary assignment procedure of multiple regression,it is found that the higher the atten-tion of the central government,the closer the geographical location,and the greater the gap in eco-nomic development level,the more conducive to regional emission reduction coordination.The cen-tral government should balance policy concerns,adhere to quantitative targets and structural optimi-zation,and implement policies according to role positioning.
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