The Evolution of Research Methods in the Digital Humanities Perspective:A Quantitative Analysis Based on CNKI Data and a Large Language Model
[Purpose/significance]This paper aims to explore the evolution trend of research methods in the field of digi-tal humanities with the help of large language model technology.[Method/process]This paper mainly focuses on the da-ta 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 com-plex abstract data.Analyzing the evolution trend in chronological order,it is found that research methods such as"in-terview 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 humanitiesLarge language modelGLM-4promt engneeringChain of Thoughtmachine learning
万方数据
维普
