Paper
12 January 2023 Data mining for news content: a case of Cantonese opera news topic modelling analysis
Bifeng Wang, Xiaotong Xu, Haocih Chen, Xinyi Xie, Jiawei Chen, Qian Liu, Yong Fu
Author Affiliations +
Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 1250914 (2023) https://doi.org/10.1117/12.2656041
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China
Abstract
Topic modelling approach is widely used for text data mining in NLP(Natural Language Processing). Text mining has been used for analysis of ICH (intangible cultural heritage), where Cantonese opera is a representative ICH of Lingnan culture. This study retrieved news content on Cantonese Opera and used machine learning analysis (LDA topic modelling) method to find out the distribution of the topics. Four main themes are concluded: the development, cooperation, and inheritance of Cantonese opera(taken up to 45.1% in all data); The traditional form(23.5%); Innovative forms(18.3%); Education and cultural inheritance of Cantonese opera(13.2%). This research further explored how to better promote Cantonese opera by analysing the topics as well as the data, and suggested that emphasis should be placed on the innovation of traditional elements in Cantonese opera, keeping them close to life, and education.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bifeng Wang, Xiaotong Xu, Haocih Chen, Xinyi Xie, Jiawei Chen, Qian Liu, and Yong Fu "Data mining for news content: a case of Cantonese opera news topic modelling analysis", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 1250914 (12 January 2023); https://doi.org/10.1117/12.2656041
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KEYWORDS
Modeling

Data mining

Machine learning

Cultural heritage

Data modeling

Analytical research

Mining

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