Abstract: 【Purpose/significance】In order to enhance the applicability and the topic inspiration of scientific research results, the pa⁃ per explores the synergistic relationship between scientific research results on the ecological governance of network information. 【Method/process】Using the BERTopic topic modelling method, the paper identifies the overall and stage topic types and their evolu⁃ tion trends for academic papers on CNKI and representative topics on Sina Weibo, and calculates the synergistic relationship by using the Word2vec model.【Result/conclusion】The degree of synergy between tweet topics and research topics is low, the synergy relation⁃ ship is lagging behind, and the type of synergy is unbalanced; in the future, academics should promote the research on personality rights protection, strengthen the research on platform information distribution, and realize the cross-research on hot topics.【Innova⁃ tion/limitation】The paper forms a more scientific description of the overall distribution, temporal characteristics, and synergistic rela⁃ tionship of scientific research themes, and provides a more systematic framework for the synergistic analysis of netizen demand; it fails to analyze the internal synergistic relationship between scientific research themes and netizen demand themes, and the evolution of the relationship between themes of the same type.