春秋时期社会发展的主题挖掘与演变分析——以《左传》为例

Purpose/significance] In the context of the rapid development of humanistic computing, this paper uses text mining technology to cluster Zuo Zhuan, which provides a reference for quantitative analysis such as topic mining in Spring and Autumn Period, and has a certain reference significance for multi-dimensional reorganization and analysis of classical texts. [Method/process] This paper uses text clustering method to analyze Zuo Zhuan quantitatively in many dimensions, breaking the linear and chronological record order of Zuo Zhuan. Firstly, using the word matching algorithm, the corpus of each vassal state is obtained from the characteristic words of Zuo Zhuan. Then the LDA topic model is used to process the characteristic words of Zuo Zhuan and the corpuses of selected vassal states. Finally, the topic strength calculation is performed in combination with the time information. [Result/conclusion] The experimental results show that the development of the Spring and Autumn Society and the vassal states can be explored according to the theme-word distribution. The development trend of the Spring and Autumn Society and various vassal states can be summarized through the theme intensity curve. Through the LDA topic clustering method, the development of war, politics and diplomacy in the whole society and different vassal states in the Spring and Autumn Period is finally revealed.