To explore the status of safe carbon reduction in China's mining industry, the data envelopment analysis (DEA) method was used to measure the safe carbon reduction efficiency of mining industry in 30 provincial-level administrative regions of China from 2014 to 2022. Additionally, social network analysis (SNA) method was utilized to examine the spatial correlation network characteristics in detail. The results reveal that the overall efficiency of safe carbon reduction in China's mining industry exhibits a growth trend with relatively small regional disparities, indicating the green transformation of the mining industry is moving towards a balanced and coordinated safe carbon reduction direction. In terms of the spatial correlation network, while there are some interactions among provincial-level administrative regions, the overall connectivity is weak, and interaction frequency needs improvement. Further analysis shows that different regions play distinct roles in spatial spillover effects. Certain provinces occupy key positions in the network, demonstrating high centrality and significant roles as structural holes and intermediary holes. Moreover, while intra-regional connections are relatively strong, the collaborative effects between regions still have room for enhancement. The research results provide a novel perspective for comprehensively understanding the status of safe carbon reduction in China's mining industry and offers scientific guidance for optimizing policy design and promoting regional collaborative development.