Scene clusters, causes, spatial patterns and strategies in the cultural landscape heritage of Tang Poetry Road in Eastern Zhejiang based on text mining

Abstract

The burgeoning field of digital humanities has provided important modern technological means for text mining in literary works. Chinese classical poetry, as a treasure in the world’s artistic treasury, holds significant value in recognizing the heritage of world culture. In this study, taking the 1589 Tang poems from the Tang Poetry Road in Eastern Zhejiang as an example, we constructed a research framework that explores the aesthetics of classical Chinese poetry landscapes and spatial imagery at the urban agglomeration scale by utilizing geographic and analytical tools such as Python programming, Gephi co-occurrence semantic networks, and GIS kernel density analysis. The framework exhibits three key innovations: (1) a text processing approach that treats individual characters as semantic units in ancient poetry texts, (2) a combined approach of Python programming techniques and Gephi visualization tool for social network analysis, and (3) a study focusing on the integration of textual and spatial aspects of literary landscape heritage corridors at the urban cluster scale. The constructed framework greatly enhances the efficiency and accuracy of Tang poetry text mining, it enables the extraction of natural and cultural landscape spatial imagery along the Tang Poetry Road, the construction of scene depictions, the identification of key regions within the scenes, and the derivation of location-specific strategies. This study broadens the scope of exploring the cultural heritage value of Tang poetry literature and provides practical guidance for the development of cross-regional heritage corridors.