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© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Quantitative cultural studies have witnessed a surge with the rapid development of computer technology in recent years. Since ancient literature constitutes a long-time-span repository for human culture, with quantitative methods and ancient texts, scholars can study the genesis and progression of human history and society across historical epochs from digital perspectives. Nevertheless, traditional humanities scholars often lack the requisite technical skills, creating a demand for interactive platforms. This paper introduces the Evol platform—an online tool designed for the quantitative analysis of ancient literature. Equipped with various analysis functions and visualization tools, the Evol platform allows users to quantify literary documents through intuitive online interaction. Using this platform, we investigated three cases of cultural evolution in ancient Chinese history: (1) the changing attitude of the government towards nomadic ethnic groups; (2) the formulation and propagation of an allusion phrase related to the Battle of Muye; (3) the influence of the Book of Changes across diverse cultural domains. By showcasing cases across diverse semantic units and topics, Evol demonstrates its potential in providing efficient and low-cost experimental tools catering to the realms of culturomics, history, and philology.

Details

Title
Evol project: a comprehensive online platform for quantitative analysis of ancient literature
Author
Wang, Jun 1 ; Duan, Siyu 2 ; Fu, Binghao 2 ; Gao, Liangcai 3 ; Su, Qi 4 

 Peking University, Department of Information Management, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Peking University, Center for Digital Humanities, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Peking University, Institute for Artificial Intelligence, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
 Peking University, Department of Information Management, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Peking University, Center for Digital Humanities, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
 Peking University, Wangxuan Institute of Computer Science, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
 Peking University, Center for Digital Humanities, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Peking University, Institute for Artificial Intelligence, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319); Peking University, School of Foreign Languages, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
Pages
291
Publication year
2024
Publication date
Dec 2024
Publisher
Palgrave Macmillan
e-ISSN
2662-9992
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2929318830
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.