The Evolution of Research Methods in the Digital Humanities Perspective:A Quantitative Analysis Based on CNKI Dataand a Large Language Model

Authors

Guangyao SUN, 1.School of Information Management, Nanjing Agricultural University, Nanjing 210095 2.Research Center for Humanities and Social Computing, Nanjing Agricultural University, Nanjing 210095
Dongbo WANG, 1.School of Information Management, Nanjing Agricultural University, Nanjing 210095 2.Research Center for Humanities and Social Computing, Nanjing Agricultural University, Nanjing 210095

Keywords

digital humanities; Large language model; GLM-4; promt engneering; Chain of Thought; machine learning

Abstract

[Purpose/significance]This paper aims to explore the evolution trend of research methods in the field of digital humanities with the help of large language model technology. [Method/process]This paper mainly focuses on the data of CNKI journal articles, selects the general Chinese large language model GLM-4, uses prompt engineering and chain of thought to extract and cluster the abstract data, of papers and analyzes its evolution trend through quantitative processing. [Result/conclusion]The study shows that GLM-4 can well identify and extract research methods from complex abstract data. Analyzing the evolution trend in chronological order, it is found that research methods such as "interview survey" and "grounded theory" are gradually marginalized, while machine learning and other related research methods are gradually becoming mainstream. This article reveals the evolution trend of research methods in the field of Chinese digital humanities, and gives the research results of digital humanities a richer and more comprehensive cultural connotation.

Digital Object Identifier (DOI)

10.19809/j.cnki.kjqbyj.2025.01.006

Recommended Citation

SUN, Guangyao and WANG, Dongbo (2025) "The Evolution of Research Methods in the Digital Humanities Perspective:A Quantitative Analysis Based on CNKI Dataand a Large Language Model," Scientific Information Research: Vol. 7: Iss. 1, Article 6.
DOI: 10.19809/j.cnki.kjqbyj.2025.01.006
Available at: https://eng.kjqbyj.com/journal/vol7/iss1/6