Microblog Sentiment Analysis Based on Dynamic Character-Level and Word-Level Features and Multi-Head Self-Attention Pooling

To address the shortcomings of existing deep learning models and the characteristics of microblog speech, we propose the DCCMM model to improve the effectiveness of microblog sentiment analysis.The model employs WOBERT Plus and ALBERT to dynamically encode character-level text and word-level text, respectively.Then, a convolution operation is used

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