<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Tea culture is the main component of Chinese traditional culture, and the analysis of tea culture dissemination paths can promote the process of Chinese traditional culture dissemination to the outside world. This paper standardizes the tea culture dissemination paths based on the principal component analysis method. The correlation matrix of the standardized data is tested for sampling suitability, and the eigenvalues and eigenvectors are calculated to derive the principal components. The variance contribution rate and the cumulative contribution rate of the variance of the principal components are calculated, and then the scores of each principal component are derived and evaluated comprehensively. Accordingly, the main communication paths of tea culture are new media communication, museum collection and exhibition, and tea trade. Based on this, this paper analyzes the communication effects of the communication paths, and the results show that: the number of followers of public accounts related to tea culture reached 63,214 in 2021, an increase of nearly 24% compared with 2019. The total number of visitors to the museum collection and exhibition of tea culture was 28,004 in 2021, an increase of 22.7% compared with the previous year. The number of tea exports and export countries both increased significantly in 2021 compared with 2012. It can be seen that the main dissemination paths of tea culture obtained by the principal component analysis method are effective for the dissemination of tea culture and also provide a reference meaning for the dissemination of other traditional Chinese culture.</p>
</abstract>

Tea culture is the main component of Chinese traditional culture, and the analysis of tea culture dissemination paths can promote the process of Chinese traditional culture dissemination to the outside world. This paper standardizes the tea culture dissemination paths based on the principal component analysis method. The correlation matrix of the standardized data is tested for sampling suitability, and the eigenvalues and eigenvectors are calculated to derive the principal components. The variance contribution rate and the cumulative contribution rate of the variance of the principal components are calculated, and then the scores of each principal component are derived and evaluated comprehensively. Accordingly, the main communication paths of tea culture are new media communication, museum collection and exhibition, and tea trade. Based on this, this paper analyzes the communication effects of the communication paths, and the results show that: the number of followers of public accounts related to tea culture reached 63,214 in 2021, an increase of nearly 24% compared with 2019. The total number of visitors to the museum collection and exhibition of tea culture was 28,004 in 2021, an increase of 22.7% compared with the previous year. The number of tea exports and export countries both increased significantly in 2021 compared with 2012. It can be seen that the main dissemination paths of tea culture obtained by the principal component analysis method are effective for the dissemination of tea culture and also provide a reference meaning for the dissemination of other traditional Chinese culture.

Analysis of tea culture communication path based on the principal component analysis method

Fujian Agriculture and Forestry University

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Tea culture is the main component of Chinese traditional culture, and the analysis of tea culture dissemination paths can promote the process of Chinese...

Analysis of tea culture communication path based on the principal component analysis method

Published Online: Apr 28, 2023

Page range: -

Received: Jun 15, 2022

Accepted: Sep 21, 2022

DOI: https://doi.org/10.2478/amns.2023.1.00101

Keywords
Principal component analysis, Tea culture communication path, Sampling suitability test, Covariance matrix, Variance contribution ratio

© 2023 Da Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of tea culture communication path based on the principal component analysis method

Published Online: Apr 28, 2023

Page range: -

Received: Jun 15, 2022

Accepted: Sep 21, 2022

DOI: https://doi.org/10.2478/amns.2023.1.00101

KeywordsPrincipal component analysis, Tea culture communication path, Sampling suitability test, Covariance matrix, Variance contribution ratio

© 2023 Da Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Principal component analysis, Tea culture communication path, Sampling suitability test, Covariance matrix, Variance contribution ratio