Research Article
Microblog Public Opinion Communication Analysis Based on Data Mining
@INPROCEEDINGS{10.4108/eai.2-12-2022.2328063, author={Xiang Li}, title={Microblog Public Opinion Communication Analysis Based on Data Mining}, proceedings={Proceedings of the 2nd International Conference on Information, Control and Automation, ICICA 2022, December 2-4, 2022, Chongqing, China}, publisher={EAI}, proceedings_a={ICICA}, year={2023}, month={3}, keywords={data mining; text analysis; time series analysis; weibo public opinion;}, doi={10.4108/eai.2-12-2022.2328063} }- Xiang Li
Year: 2023
Microblog Public Opinion Communication Analysis Based on Data Mining
ICICA
EAI
DOI: 10.4108/eai.2-12-2022.2328063
Abstract
With the rapid development of the Internet, most users are gradually accustomed to online social networking, so social platforms have become an important way of information exchange and dissemination. The unrest, loss and impact of secondary disasters transmitted by unconventional emergencies are incalculable. Sina Weibo is a social platform widely used by many users. The platform has a large number of users. Research on the use habits and information dissemination channels of microblog users is of great significance for the early warning and intervention of network public opinion in unconventional emergencies. This paper mainly studies the information dissemination of unconventional events from the microblog text analysis, network public opinion characteristics and time series analysis. It is found that the number of microblog posts significantly affects the number of fans, the number of fans significantly affects the number of followers, and the number of followers significantly affects the total number of Weibo retweets, and the time series evolution law of "Xinjiang cotton" predicted by SPSS is consistent with the reality.