HIGHLIGHTS
SUMMARY
Text sentiment analysis technology (TSAT) refers to the semantic orientation or polarity analysis of subjective attitudes and emotions in texts using natural language processing (NLP), statistical, or machine_learning techniques. After continuous research and development, TSAT has been improved from a sentiment-dictionary-based 3 of 20 method to a machine-learning-based method, and from supervised machine_learning to deep learning. This research uses machine_learning algorithms based on attention to analyze Weibo comments with fine-grain sentiment classification through data obtained from the Shanghai Weibo platform. By analyzing the distribution characteristics of urban youth sentiments . . .
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