This project is an experimental research that aims to explore how recently developed concepts, methods, and tools of digital humanities can be applied to the study of history, to test their effectiveness, and to analyze their possible obstacles, limitations, and deficiencies. The subject of this project is the Chinese Nationalist（GMD） military elite (i.e., officers with the rank of major general and above). The core material relied is a collective biography entitled The 9,000 Generals of GMD (中国国民党九千将领), employing methods such as text mining, machine learning, and statistical analysis.
Unlike traditional historiography, which relies primarily on the thinking of the researcher, this project leaves the vast majority of analysis and synthesis to computers and software. Specifically, with the help of a data engineer, we will transform The 9,000 Generals of GMD into an analyzable corpus from which we will extract the core information needed for the project through text mining and machine learning tools, including name, date of birth, place of origin, military type, rank, position, faction, education, etc.
On this basis, and processing the data through R (R-studio, R-shiny), we shall attempt to obtain answers on the following issues:
Based on the above analysis, we can roughly build up a model to “draw” a group portrait of the military elite of the GMD. As experimental research, whether the project can produce an analysis that is closest to the military elite, and whether it can “map” the most accurate “group portrait” is not the sole purpose of importance. Its core value also lies in testing the efficiency and limitations of digital humanities concepts and methods in historical research, especially in the study of modern Chinese history.