Purpose/Significance In the context of deep digital development, digital humanities as a development field of interdisciplinary deep integration, the scientific research cooperation among scholars is becoming more and more frequent. It is necessary to analyze and excavate the increasingly complex cooperation relationship, to help scholars obtain potential cooperation opportunities to promote academic exchanges. Method/Process In this paper, scholars, institutions and keywords were used as node data, and coauthors, citations, posts and research topics were used as relational data to build scholar-collaboration graphs, which was stored based on the graph database Neo4j. Cypher query language and GDS algorithm library were used to analyze the cooperation community discovery, core scholar identification and cooperation trend prediction of scholars in the field of digital humanities. Results/Conclusion The experimental results show that Neo4j can better realize the construction and analysis of scholars' coop