At the completion of the "1+N" policy system for the "dual-carbon" target, improving carbon performance is a key to promoting balance between the environment and the economy and facilitating synergistic regional sustainability. However, the existing studies mainly focus on the measurement of carbon emission performance, influencing factors and traditional spatial scales, lacking exploration of the spatial correlation strength, network characteristics, and network conditions of various provinces and regions of carbon emission performance, and rarely examining the influencing factors of spatial network relationships from the perspective of spatial networks. Therefore, this article used the super-efficient SBM model to calculate the carbon emission performance of 30 provinces in China from 2005 to 2022. The structural characteristics of the network, transmission paths of interrelationships, network effects, and influencing factors were analyzed using the modified gravity model and social network analysis. The results are as follows: ① China's carbon emission performance increased significantly, the spatial correlation network characteristics were obvious, manifested as a dense in the east and sparse in the west pattern with the "Beijing-Shanghai" double core actors as the center, and gradually formed a complex and compact network distribution form. ② The number of relationships within each sector of the network is significantly lower than between sectors, and the direct connection and correlation between the "net spillover" and "net beneficial" sectors were strengthened. The influence of the "bidirectional spillover" and "broker" sectors has been gradually weakening. ③ The overall and individual structural characteristics of the correlation network significantly affect carbon emission performance. Increasing network density, number of relationships, degree centrality, closeness centrality, and intermediate centrality, decreasing network efficiency and network hierarchy are effective in improving carbon emission performance. ④ Reduced spatial distance and widening differences in levels of economic development, technological innovation, openness to the outside world, and urbanization among different provinces could significantly enhance the strength of network connections. The impact of differences in industrial structure, population density, environmental regulations, and energy consumption on network connection strength showed phasic characteristics. The study puts forward countermeasures and suggestions in terms of enhancing the strength of the carbon emission performance linkage network, giving full play to the network effect, and strengthening the transmission of influencing factors in the network, which have certain reference values for the country and region to improve the overall carbon emission performance and accelerate the synergistic green development in the region.