A Specific Public Sentiment Clustering Problem Based on Hybrid Bat Algorithm
Liping Jia, Zhonghua Li · 2021 17th International Conference on Computational Intelligence and Security (CIS) · 2021
With the release of the “double reduction” policy, more public sentiments about this policy have been produced on the internet. In this paper, public sentiments about “double reduction” policy is crawled from weibo and studied. After data preprocessing, a hybrid bat algorithm with K-means method is proposed to cluster this type of public sentiment problem. With the crawled data, the performance of the proposed algorithm is verified by the traditional K-means clustering method and proposed hybrid bat algorithm.