This study was conducted to suggest how Chinese classical literature researchers should respond the time when the words “fourth industrial revolution” and “AI era” became hot issues around the world. Although it is not yet clear what the meaning of the fourth industrial revolution is, many people are emphasizing the importance of “big data” and “artificial intelligence.” We need to collect ‘data' and process ‘information' to create ‘knowledge' and provide ‘better understanding' for our research. For this reason, I think that the researchers in Chinese classical literature also should adapt well to the AI era and find innovative methodologies.
In this paper, I reviewed five detailed areas to explore new methodologies in Chinese classical literature research. Computational criticism is an attempt to understand literary texts using corpus stylistics as the main methodology. Both in terms of macro-views expressed by Franco Moretti as “distant reading” and in vocabulary-level exploration are expected to be effective. Big data seems useful when trying to find meaningful information through data mining techniques. Better results are expected when linked to network analysis. Artificial intelligence can find advantages in co-occurrence analysis using text processing models such as 'Word2Vec'. The application of sentence similarity analysis will help with comparison between different versions and the creation of the authors' genealogy. Machine translation is not yet expected to be stable reading of original texts and annotations. However, it is expected to contribute to lowering the language barrier in the process of obtaining secondary data in modern languages. Information visualization does not seem to have been activated in both GIS-based literature maps and infographics fields. I hope that more active exploration and attempts will be carried out in conjunction with the field of Chinese classical literature education.
However, it is not desirable to overlook the fact that using computers in Chinese classical literature research is ultimately researchers. In other words, discovering research problems and finding solutions is human, not AI. In order to find a research problem, researchers must first read the target texts meticulously. If we have determined that “calculation” is necessary to solve research problems, it is better to find the optimal and best solution with the help of a computer expert than to solve it by ourselves.