Proceedings of the 4th International Conference on Internet, Education and Information Technology (IEIT 2024)

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Data mining of Kaiping Watchtower YouTube video comments: a machine learning approach

Authors
Bifeng Wang1, Xiaohui Sun2, Qian Liu2, *
1School of Art Education, Guangzhou Academy of Fine Arts, Guangzhou, China
2Journalism and Communication School, Jinan University, Guangzhou, China
*Corresponding author. Email: Tsusanliu@jnu.edu.cn
Corresponding Author
Qian Liu
Available Online 21 November 2024.
DOI
10.2991/978-94-6463-574-4_40How to use a DOI?
Keywords
Kaiping Watchtower; LDA theme model; theme mining
Abstract

Text data mining serves as a computational tool for analyzing Intangible Cultural Heritage (ICH). This paper focuses on the Kaiping Watchtower, a pivotal element of Guangdong culture and Kaiping’s historical narrative. The study employs machine learning techniques, specifically LDA topic modeling, to discern thematic patterns of YouTube video comments’ text. Four core themes emerge Kaiping Watchtower’s role in local life, its cultural significance within village communities, its potential as a tourism asset, and its portrayal in media productions. Furthermore, the research explores leveraging text data analysis to enhance Kaiping Watchtower’s promotion, realize the educational significance of intangible cultural heritage and promote traditional culture. It advocates for the strategic development of cultural heritage tourism, leveraging its unique attributes to guide the public to understand history while delving into its deeper cultural meanings. This approach aims to perpetuate Kaiping Watchtower’s legacy, cultivate national pride and cultural identity, guide the public to participate in the inheritance of intangible cultural heritage and safeguard its long-term preservation.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 4th International Conference on Internet, Education and Information Technology (IEIT 2024)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
21 November 2024
ISBN
978-94-6463-574-4
ISSN
2667-128X
DOI
10.2991/978-94-6463-574-4_40How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Bifeng Wang
AU  - Xiaohui Sun
AU  - Qian Liu
PY  - 2024
DA  - 2024/11/21
TI  - Data mining of Kaiping Watchtower YouTube video comments: a machine learning approach
BT  - Proceedings of the 4th International Conference on Internet, Education and Information Technology (IEIT 2024)
PB  - Atlantis Press
SP  - 341
EP  - 350
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-574-4_40
DO  - 10.2991/978-94-6463-574-4_40
ID  - Wang2024
ER  -