Rural digital transformation and its impact on agricultural carbon emission reduction based on social network analysis

This research reveals the impact of the spatial correlation network of rural digital transformation on agricultural carbon emission reduction, and provides a theoretical basis for promoting the spatial linkage of rural digital transformation to enable agricultural carbon sequestration and emission reduction. Based on the "efficiency equity" framework, with the help of carbon emission reduction potential model, social network analysis model and benchmark regression model, this paper explores the impact of rural digital transformation spatial correlation network on agricultural carbon emission reduction potential in 31 provinces (autonomous regions and municipalities) in China from 2011 to 2022. The results show that: (1) The rural digital transformation index has continued to grow, showing a decreasing pattern from eastern to central to western regions. (2) The agricultural carbon emission reduction potential index has fluctuated and risen, with a spatial characteristic of decreasing from central to eastern to western regions. (3) The spatial correlation network of rural digital transformation shows the polar core diffusion law of dense in the central region and decreasing layer by layer in the periphery, and the network density and correlation number fluctuate and rise. Shandong, Henan, Hubei and some other regions have high node centrality. (4) The node centrality of spatial correlation network of rural digital transformation has a significant positive impact on agricultural carbon emission reduction potential, and the impact has regional heterogeneity. In the future, it is essential to solidify a networked mindset to promote the coordinated spatial development of rural digital transformation, break down barriers to the sharing of low-carbon agricultural elements, and achieve a positive interaction between efficiency and equity in agricultural carbon emission reduction.