Studying Ci poetry helps enhance the appreciation of artistic expression of traditional Chinese literature. In this area of study, significant achievements were yielded during the Republican China period (1911–1949) in particular the numerous publications of Ci annotations — the explanatory notes, interpretations, and critical analyses of Ci poetry. These annotations not only provide linguistic and historical explanations but also offer insights into the meaning and writing style of Ci poetry. Despite their significance, Ci annotations have been often seen as auxiliary learning tools for the study of Ci poetry and received little attention from academia. Also, they are rarely collected by libraries over time, which makes it difficult to conduct comprehensive studies of this topic using the traditional way of information search from books and journals.
In response to these limitations, Dr Gary Tsang, Assistant Professor in the School of Arts and Social Sciences at Hong Kong Metropolitan University, conducted a research project which aims to comprehensively investigate Ci annotations in the first half of the 20th century by utilising scholarly big data — the combination of several digital archives which consist of extensive and diverse information. With the aid of scholarly big data, Dr Tsang discovered that there are about 100 Ci annotations published during the Republican China period, which is a significant growth in quantity compared to only about 30 Ci annotations from Qing dynasty or before. Most of these Ci annotations could be accessed through the internet, thus saving time and costs associated with searching for relevant books that are scattered across different libraries or not even collected by libraries. As a result, Dr Tsang could review the Ci annotations and determine their academic value more efficiently, which helped to identify the areas that lack sufficient research and forming his research directions and strategies.
Dr Tsang pointed out that some Ci annotations that were rarely discussed or nearly neglected by scholars can be found because of the facilitation of scholarly big data. Researchers are now able to overcome spatial limitations and expand the research scope by comparing different editions of Ci annotations, such differences between editions may reveal the evolution of a Ci poet's scholarly ideas. For instance, with the assistance of scholarly big data, Dr Tsang could find and access the initial edition of Yang Tiefu (楊鐵夫)'s Meng Chuang Ci Xuan Jian Shi (《夢窗詞選箋釋》) and figure out the differences between various versions of this Ci annotation, in order to study the evolution of Yang's literary and poetic thoughts.
In addition, Ci annotations published in the first half of the 20th century are important for enhancing readers' understanding of how the Ci study in Republican China inherited and transformed the styles and concepts from the late Qing period. Yu Xuan (余謇)'s Tang Song Ci Xuan Zhu Ji Ping (《唐宋詞選注集評》) is a Republican China's Ci annotation which can be preserved and disseminated with the help of scholarly big data. The author analysed Ci poetry in Tang dynasty and Song dynasty in terms of its rhythmic characteristics, such as the level and oblique tones (平仄) — the different tonal patterns used in the verses in a Ci poetry. Yu Xuan's emphasis on poetic rhythm is an example of Ci poets in the early 20th century's inheritance of “Shoulu” (守律) — a Ci poetic concept that was common in Qing dynasty meaning the adherence to established poetic conventions and structural rules in Ci composition. The use of scholarly big data benefits the study of Ci annotations which shed light on the continuity of poetic traditions and characteristics of Ci poetry.
The research of Dr Tsang contributes to demonstrating the capability of scholarly big data in facilitating in-depth studies of classical literature. His study not only expands the research scope and depth of Ci studies but also provides a new research method that can be applied to the study of other literary genres such as poetry and prose.
For more details about the research results, please refer to the following publications generated from the project:
