Text sentiment classification based on Vit-BiGRU-attention model

Xuyang Wang; Ruixin Wang

doi:10.1117/12.2659762

30 November 2022 Text sentiment classification based on Vit-BiGRU-attention model

Xuyang Wang, Ruixin Wang

Proceedings Volume 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022); 124561L (2022) https://doi.org/10.1117/12.2659762
Event: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 2022, Qingdao, China

Abstract

Nowadays, more and more users are playing an important role on the Internet. The more comments they post, the more information they contain and the more informative they are. In order to analyze the sentiment orientation of users' comments more accurately, the text Vit-BiGRU-Attention sentiment classification model is based on BiGRU and Attention mechanisms. First, the CBOW model is used to train the word vector. Second, BiGRU is combined with Viterbi algorithm to extract contextual features of the text by combining forward and backward hidden layers. Then, different weights are assigned to words by the attention mechanism to enhance the understanding of emotions and determine the polarity of emotions. Finally, the output is passed through a softmax classifier. The experimental results show that the accuracy of the model has been greatly improved.

Citation Download Citation

Xuyang Wang and Ruixin Wang "Text sentiment classification based on Vit-BiGRU-attention model", Proc. SPIE 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 124561L (30 November 2022); https://doi.org/10.1117/12.2659762

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