Hot Spot Mining and Analysis Model of Sports Microblog Culture Public Opinion Based on Big Data Environment
Qingyong He · 2021 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) · 2021
By analyzing the development characteristics of sports microblog cultural public opinion under the big data environment and the specific needs of automatic public opinion monitoring, the paper designs a sports microblog cultural public opinion hotspot mining system structure model, and describes the main functions and implementation methods of each layer. The paper first uses tools such as ICTCLAS and AntConc to extract hot words, then describes the standardized data representation, and finally uses the Chameleon clustering algorithm to achieve clustering and topic extraction of hot blog posts. This method will provide information support for timely discovering sensitive information and grasping the hot spots of sports microblog culture and public opinion.