Amidst the rapid pace of urban development, rural communities continually face the challenges posed by erratic natural disasters and human-induced disturbances. Evaluating and improving the resilience of rural areas is crucial for achieving sustainable development. Examining the rural network framework serves as a method to achieve rural resilience. This study established a contact network encompassing 13 villages in Shiba town, Mingguang City, through the collection of time-distance data, questionnaire interview data, and map vector data to examine the spatial patterns of the rural network. The examination of structural resilience was conducted through the framework of complex network theory. The examination of the network's transitivity and diversity through the frameworks of hierarchy, matching, transitivity, and aggregation reveals its resilience to disruption simulations, such as node failure. The findings indicate that the network exhibits a configuration marked by a dense central region, sparse connections in the north, and a lack of connectivity in the south. The network exhibits a flat structure, with nodes that are relatively uniform in nature. The network exhibits significant disassortativity, classifying it as a disassortative network, where villages with higher node degrees tend to connect with those having lower node degrees. The local transitivity of the network is significantly elevated, with approximately 90% of settlements necessitating just one transfer to establish direct communication. The network exhibits significant clustering effects, marked by robust connections among villages and a few isolated node villages. The transitivity of the network and its diverse spatial patterns show markedly different characteristics when subjected to interruption simulation. The study identified two primary nodes and one susceptible node. The findings from the study precisely reflect the characteristics of the rural network. This can provide theoretical perspectives for analyzing the resilience of rural network structures and support decision-making in rural planning and development.
