SHS Web Conf.
Volume 157, 20232022 International Conference on Educational Science and Social Culture (ESSC 2022)
|Number of page(s)||4|
|Section||Human Behavioural Science and Social Development|
|Published online||13 February 2023|
A Case Study of Chinese Sentiment Analysis of Social Media Reviews Based on LSTM
1 Department of Plasma Physics and Fusion Engineering and CAS Key Laboratory of Geospace Environment, University of Science and Technology of China, Hefei, Anhui 230026, People’s Republic of China
2 Key Laboratory of Computational Linguistics, Perking University, People’s Republic of China
* Corresponding author: firstname.lastname@example.org
Network public opinion analysis is obtained through a combination of natural language processing (NLP) and public opinion supervision, and is crucial for monitoring public mood and trends. Therefore, network public opinion analysis can identify and solve potential and budding social problems. This study aims to realize an analysis of Chinese sentiment in social media reviews using a long short-term memory network (LSTM) model. A dataset was obtained from Sina Weibo using a web crawler and cleaned using Pandas. First, Chinese comments regarding the legal sentencing in of Tangshan attack and Jiang Ge Case were segmented and vectorized. Thereafter, a binary LSTM model was trained and tested. Finally, sentiment analysis results were obtained by analyzing the comments with the LSTM model. The accuracy of the proposed model has reached approximately 92%.
© The Authors, published by EDP Sciences, 2023
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