Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 10, Issue 1


Published
on

March 24, 2025


Pages


DOI

Article

Research on Symbolic Expression and Digital Design Methods of Intangible Cultural Heritage Based on Big Data Analysis

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Authors

Hui Zhang Affiliation:
Yangzhou Industrial Technical College of Art and Design, Yangzhou, Jiangsu, 225000, China.


Abstract

Based on semiotics theory, combined with Peirce’s ternary semiotics model, the study systematically analyzes the translation process of intangible cultural heritage (ICH) symbols, and explores how to balance ICH cultural heritage and digital innovation design in the process of symbol translation. Using the big data analysis method, the study analyzes the symbolic expression of intangible cultural heritage, the path of symbolic translation, and the effects of digital communication. The study shows that the degree of embodiment of the four symbolic elements, namely, pattern symbol, historical origin, tea ordering technique and spiritual connotation, in the digitalized Tea Hundred Operas is rated between 4.09 and 4.58. In this paper, the digital design of non-heritage has a better user experience, with the experience dimensions such as aesthetics and functionality rated above 9 points. Digital design can promote the dissemination of non-heritage culture at the cognitive, attitudinal, and behavioral levels. The big data analysis method used in this paper has better performance in recognizing the sentiment of user comments, with the recognition accuracy rate higher than 93%, and by analyzing the sentiment of user comment text, we know that the user’s satisfaction with the digital design of NRLs in this paper is about 4.2 points.


Keywords

Intangible cultural heritage, Symbolic expression, Digital communication, Tea Hundred Opera, 68T09


Citation

Zhang, H. (2025). Research on symbolic expression and digital design methods of intangible cultural heritage based on big data analysis. Applied Mathematics and Nonlinear Sciences, 10(1). https://doi.org/10.2478/amns-2025-0719

Published by: Engineering Journals

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