This study aims to explore knowledge structure and research trends in the domain of digital humanities (DH) in the recent decade. The study identified prevailing topics and then, analyzed trends of such topics over time in the DH field.
Research bibliographic data in the area of DH were collected from scholarly databases. Multiple text mining techniques were used to identify prevailing research topics and trends, such as keyword co-occurrences, bigram analysis, structural topic models and bi-term topic models.
Term-level analysis revealed that cultural heritage, geographic information, semantic web, linked data and digital media were among the most popular topics in the recent decade. Structural topic models identified that linked open data, text mining, semantic web and ontology, text digitization and social network analysis received increased attention in the DH field.
This study applied existent text mining techniques to understand the research domain in DH. The study collected a large set of bibliographic text, representing the area of DH from multiple academic databases and explored research trends based on structural topic models.
Digital Object Identifier (DOI)
Joo, Soohyung; Hootman, Jennifer; and Katsurai, Marie, "Exploring the Digital Humanities Research Agenda: A Text Mining Approach" (2021). Information Science Faculty Publications. 100.