Implementation Sentences Attention Mechanism in Online Reviews

Sentiment analysis involves recognizing the opinions expressed within a piece of text. Sentiment analysis classifies comments as positive, negative, or neutral. The Majority of researchers in this field are based on word-level attention. We believe sentences are an important part of the text, therefore, they must have different weights. Hence In this paper, we introduce a sentence attention mechanism (SAM) that utilizes multi-head self-attention to enhance the performance of sentiment analysis models by effectively capturing contextual relationships within sentences for improved interpretability and accuracy in classification tasks. We carried out multiple sentiment analysis experiments across various domains, including multi-domain, cross-domain, and domain-specific approaches, using real-world datasets. The results of these experiments demonstrate that the proposed method outperforms other basic models and achieves higher accuracy. The accuracy of the model is 0.68