Abstract: The continuous advancement of economic globalization and informatization, along with the rapid construction of transportation infrastructure, have made cities more closely connected and made urban networking a prominent trend. Network news is easily accessible and contains bundant geographical information. Studying urban networks from the view of toponym co-occurrences in the news is a brand-new perspective, and conclusions may help clarify the status of cities, deepen the understanding of the structure of urban networks. This paper conducts research from contact, node and network successively. Firstly it proposes a new method aiming at measuring relatedness of city pair based on toponym co-occurrences; then it uses the centrality of social network analysis to characterize urban influence and explores its spatial distribution; finally it studies the characteristics and structure of urban networks. Results show that the proposed measurement approach highlights the strength of the relatedness, and makes up for the shortcomings of Ochiia coefficient method such as ignoring multiple diverse toponyms in the news; coastal cities possess higher urban influence than inland ones; the backbone urban network presents an approximately diamond-shaped spatial structure, metropolises such as Beijing, Shanghai, Guangzhou, and Chongqing are the core nodes.