To investigate the spatial interaction effect and nodal attractions of cities, a set of inter-city social network location-based check-in data with a time span of one year among 348 municipal cities in China is examined with a PSO (Particle Swarm Optimization) method and the gravity model. Twelve variables related with economic development, industrial structure, population scale and structure, tourism competitiveness and educational level are introduced to further investigate their influences on nodal attractions of cities. The results indicate a distance decay effect which is relatively weaker than in other systems, suggesting that human mobility at the regional level is less sensitive to the change in geographic distance. A close examination of the nodal attractions suggests variables related to the cities’ tourism competitiveness, maturity of development and population scale significantly influence the value of nodal attractions. This article will serve as a stepping-stone for a better future understanding of human travel pattern, check-in behaviors and the real meaning of nodal attractions in some complicated networks.