Based on the modified gravity model, a spatial correlation network of innovation was constructed among cities in Guangdong, China. Social network analysis was employed to explore their evolution characteristics during 2009–2017. The results indicate that the innovation output of prefecture-level cities in Guangdong Province shows both spatial correlations and differences. Their network shows lower density, higher efficiency, and rigid stratification properties. Based on small cluster analysis, these cities are classified into four blocks, the members of which changed. In 2017, four well-defined subgroups formed, which are “bidirectional spillover plate”, “main spillover plate”, “net beneficial plate”, and “agent plate”. With this network, the geographical characteristics of the innovation capabilities and differences among the cities in Guangdong, as well as the different positions and roles of each city in the associated network, can be properly understood. Consequently, the transmission mechanisms and development strategies of innovation in Guangdong Province can be better explored.

These data originate from the 2009–2018 Guangdong Statistical Yearbook on Science and Technology, Guangdong Intellectual Property Yearbook and the statistical bulletins of various prefecture-level cities in Guangdong. 

Based on the modified gravity model, a spatial correlation network of innovation was constructed among cities in Guangdong, China by these data. Social network analysis was employed to explore their evolution characteristics during 2008–2017.