Result: 数字人文 野一手证据冶 循证范式研究院 基于 叶鲍氏国策曳 的共词分析.

[Purpose/Significance] Evidence acquisition is one of the most critical factors affecting evidence-based digital humanities research. The first-hand evidence contained in the ancient literature works is an important way to carry out digital humanities research, and thus, the purpose of this research is to shed light on the evidence-based digital humanities research process based on the empirical analysis of Bao's Zhan Guo Ce, which is one of the most influential books in Chinese history. [Method/Process] In the face of rich and diverse Chinese ancient literature works, it is of theoretical and practical value to build an independent knowledge system with Chinese characteristics based on the evidence-based paradigm of digital humanities. For this reason, the present research used the natural language processing (NLP) method to analyze Bao's Zhan Guo Ce in Jiayan Library, which is tailored for the NLP analysis of Chinese ancient literature works. By using co-word analysis, this research comprehensively discusses how digital humanities researchers carry out systematic research based on first-hand evidence from ancient literature via word frequency analysis, visualization of co-words, cluster analysis, centrality degree analysis, etc. Social network analysis (SNA), NetworkX algorithm and co-word visualization procedure are applied to give us insight into how to extract the first-hand evidence from ancient literature works. [Results/Conclusions] The key results include a procedure on how to extract first-hand evidence from ancient literature works like Bao's Zhan Guo Ce, in digital humanities research via Python. Specifically, the procedure includes basic word frequency indicators, a tool of removal of stop words, process of recognition and removal of ambiguous words. Furthermore, this study also takes Bao's Zhan Guo Ce as an example to show the basic procedure of analyzing first-hand evidence in digital humanities research by using a series of statistical analysis methods and indicators such as co-word network visualization, clustering coefficient, centrality degree, and structural hole recognition. The procedures, tools and methods demonstrated in this study are expected to provide reference for completing the evidence-based digital humanity research paradigm of first-hand evidence. Thus, the procedures, tools, statistical indicators and algorithm demonstrated in this research are expected to provide a foundation for building an independent knowledge system of evidence-based digital humanities with Chinese characteristics. [ABSTRACT FROM AUTHOR]

［目的 / 意义］蕴藏于原始文献典籍的"一手证据"是展开数字人文研究的重要途径。［方法 / 过程］本文以 《鲍氏国 策》 为例, 基于自然语言处理技术, 以共词分析方法为突破口, 比较全面地展开了数字人文研究者如何基于来自原始文献的 "一手证据"展开系统化的研究。［结果/结论］本研究针对 叶鲍氏国策曳 中"一手证据"的提取, 从词频统计、停用词的去 除、词义模糊词的识别与剔除等方面, 展开了基于词语展开分析时若干基础指标的获取过程;进而, 本研究以 《鲍氏国策》 为例, 提供了数字人文研究中, 应用共词网络可视化、聚类系数、中心度指标、结构洞识别等一系列统计分析方法与指标, 对一手证据展开解析的基本程序。本研究所展开的方法, 有助于为完成数字人文"一手证据"的循证范式提供参考. [ABSTRACT FROM AUTHOR]