The rapid bi-level exploration on the evolution of regional solar energy development

•Bi-level networks are classified.•Economic region are used to explain the results.•Practical information is explored as the market feedback.•Combined approaches are used to quickly acquire information.•Visualized evolution of local solar energy development in China is provided.

As one of the renewable energy, solar energy is experiencing increased but exploratory development worldwide. The positive or negative influences of regional characteristics, like economy, production capacity and allowance policies, make them have uneven solar energy development. In this paper, we aim at quickly exploring the features of provincial solar energy development, and their concerns about solar energy. We take China as a typical case, and combine text mining and two-actor networks. We find that the classification of levels based on certain nodes and the amount of degree avoids missing meaningful information that may be ignored by global level results. Moreover, eastern provinces are hot focus for the media, western countries are key to bridge the networks and special administrative region has local development features; third, most focus points are more about the application than the improvement of material. The exploration of news provides practical information to adjust researches and development strategies of solar energy. Moreover, the bi-level exploration, which can also be expanded to multi-level, is helpful for governments or researchers to grasp more targeted and precise knowledge.