Historical social network analysis has gained significant academic attention in the emerging field of digital humanities.This study introduces a framework that utilizes a combination of explicit and implicit network representations to mine knowledge from historical figure relationships.It integrates heterogeneous data through data extraction to create a unified historical figure relationship dataset,enabling multidimensional analysis of historical networks.A network representation learning algorithm is used to generate figure vectors for semantic computing tasks and empirical analysis.A knowledge service platform is then developed to help humanities scholars in exploring the social connections and activities of historical figures related to their academic interests.
关键词
历史社会网络分析/网络表示学习/知识发现/数字人文
Key words
Social network analysis/Network representation learning/Knowledge discovery/Digital humanities
维普
万方数据