基于图数据库Neo4j的学者合作图谱分析——以数字人文领域为例

Purpose/Significance] In the context of deep digital development, digital humanities as adevelopment field of interdisciplinary deep integration, the scientific research cooperation among scholarsis becoming more and more frequent. It is necessary to analyze and excavate the increasingly complexcooperation relationship, to help scholars obtain potential cooperation opportunities to promote academicexchanges. [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-collaborationgraphs, which was stored based on the graph database Neo4j. Cypher query language and GDS algorithmlibrary were used to analyze the cooperation community discovery, core scholar identification and cooperationtrend prediction of scholars in the field of digital humanities. [Results/Conclusion] The experimental resultsshow that Neo4j can better realize the construction and analysis of scholars cooperation network in the fieldof digital humanities. It can help scholars quickly find interdisciplinary scholars who are highly related totheir research interests and directions among many researchers, so as to promote scholars cooperation anddiscipline development in the field of digital humanities.