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Network public opinion analysis is obtained by a combination of naturallanguage processing (NLP) and public opinion supervision, and is crucial formonitoring public mood and trends. Therefore, network public opinion analysiscan identify and solve potential and budding social problems. This study aimsto realize an analysis of Chinese sentiment in social media reviews using along short-term memory network (LSTM) model. The dataset was obtained from SinaWeibo using a web crawler and was cleaned with Pandas. First, Chinese commentsregarding the legal sentencing in of Tangshan attack and Jiang Ge Case weresegmented and vectorized. Then, a binary LSTM model was trained and tested.Finally, sentiment analysis results were obtained by analyzing the commentswith the LSTM model. The accuracy of the proposed model has reachedapproximately 92%.

A Case Study of Chinese Sentiment Analysis on Social Media Reviews Based on LSTM