Version 1
: Received: 11 October 2024 / Approved: 17 October 2024 / Online: 17 October 2024 (11:32:43 CEST)
How to cite:
Hu, W.; Wang, W.; Qu, C.; Li, R. Constructing a Dynamic Monitoring and Analysis Platform for the International Mainstream Media Corpus on China’s Image. Preprints2024, 2024101364. https://doi.org/10.20944/preprints202410.1364.v1
Hu, W.; Wang, W.; Qu, C.; Li, R. Constructing a Dynamic Monitoring and Analysis Platform for the International Mainstream Media Corpus on China’s Image. Preprints 2024, 2024101364. https://doi.org/10.20944/preprints202410.1364.v1
Hu, W.; Wang, W.; Qu, C.; Li, R. Constructing a Dynamic Monitoring and Analysis Platform for the International Mainstream Media Corpus on China’s Image. Preprints2024, 2024101364. https://doi.org/10.20944/preprints202410.1364.v1
APA Style
Hu, W., Wang, W., Qu, C., & Li, R. (2024). Constructing a Dynamic Monitoring and Analysis Platform for the International Mainstream Media Corpus on China’s Image. Preprints. https://doi.org/10.20944/preprints202410.1364.v1
Chicago/Turabian Style
Hu, W., Chenghao Qu and Ruitian Li. 2024 "Constructing a Dynamic Monitoring and Analysis Platform for the International Mainstream Media Corpus on China’s Image" Preprints. https://doi.org/10.20944/preprints202410.1364.v1
Abstract
This article reports on the development of a big data processing platform that uses hot words(politics, economy, military, culture and society) reflecting the national image as the search object and the key time points as the time domain of data resources. The platform crawls (in real time), continuously expands and dynamically monitors a corpus of mainstream media covering China in developed countries (including the United States, Britain, Germany, France and Japan) and in developing countries (such as Brazil, India and South Africa). In this study, the principles of platform development and operation and the software and hardware operating environment were determined.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.