The Sentiment Attitude of Weibo Users towards Annual Individual Income Tax Return: Based on Natural Language Processing and Machine Learning Methods

This passage discusses a study that collected Weibo posts from different users related to China’s Annual Individual Income Tax Return(AIITR), and compared the performance of six machine learning models (support vector machine, random forest, naive Bayes, K-nearest neighbor, decision tree, and logistic regression), as well as a deep learning LSTM model, to choose the more accurate LSTM model for sentiment analysis. The study aims to explore the compliance status of individuals in tax-paying and uses the Latent Direct Allocation (LDA) model to display the topics discussed in the Weibo posts, in order to gain a deeper understanding of the issues that Weibo users are concerned about related to AIITR, and provide policy recommendations.