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Exploring the application of multidimensional data analysis in cross-cultural communication exchange research
- Source :
- Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
- Publication Year :
- 2024
- Publisher :
- Sciendo, 2024.
-
Abstract
- Five thousand years of culture, precipitated by the wisdom of the Chinese people, is an important carrier of dialog and exchange between China and the world. At present, various data analysis methods are emerging and providing solutions to different research problems from a higher perspective. In this paper, through the construction of the Patterntrack multidimensional data analysis model, multidimensional scale analysis is introduced to process multidimensional data so as to achieve the requirement of an accurate analysis of cross-cultural communication and exchange. In the analysis of cross-cultural communication exchanges between Confucianism and Taijiquan, both of them come to conclusions that correspond to the actual situation. When testing the data set of cross-cultural communication and exchange on social platforms, the clustering effect of Patterntrack multidimensional data analysis is ranked first, with RI=0.8208, FMI=0.9223, and JC=0.813, which is much higher than that of the second-ranked clustering effect of the DBSCCAN analysis method. After optimizing the influencing factors analyzed by Patterntrack multidimensional data analysis, the number of visits to the website is 150% higher than that before the optimization, the amount of forwarding is improved to 71.69%, the number of clicks on the content after forwarding reaches 1,056, and the average number of times of reading for each article in the website reaches 3.1, which proves that after optimizing the relevant influencing factors, the attractiveness of the content is greatly improved.
Details
- Language :
- English
- ISSN :
- 24448656
- Volume :
- 9
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Applied Mathematics and Nonlinear Sciences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.6f55328f69a54e3cb26e99d6705d60f0
- Document Type :
- article
- Full Text :
- https://doi.org/10.2478/amns-2024-1731