LitRank: An Interactive Tool for Ranking and Field Inference in Literary Data
Hongxin Fu, Ning Zhang, Chengtao Ji, Lijie Yao, Wei Li · 2025
Advancements in digital humanities have enabled new approaches to analyzing literary works. However, challenges arise in managing fragmented historical records, complex relationships, and multidimensional data, including timelines, locations, and interpersonal connections. This paper introduces LitRank, a visualization tool designed to explore 431 historical Chinese collections. LitRank evaluates the literary impact of collections and writers using role-based author contributions and defined metrics like authorship, commentary mentions, and biographical records. It also helps experts focus on addressing critical data gaps by identifying records with high literary impact and significant missing fields. Furthermore, LitRank infers missing temporal details and uncovers potential kinships among co-authors by analyzing shared surnames and collaboration patterns, providing deeper insights into the literary corpus.