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September 10, 2025Scientific ReportsOpen Access

Aspect-level multimodal sentiment analysis model based on multi-scale feature extraction

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This research demonstrates improved accuracy in sentiment analysis using BERT and image features, suggesting enhanced classification effectiveness.

The AMSAM-MFE model significantly improved accuracy and F1 scores in aspect-level multimodal sentiment analysis tasks.
By utilizing multi-scale feature extraction from both text and images, superior classification effectiveness was achieved.
The model incorporated a Multi-scale Layer based on BERT for text and a Resnest269 model for image feature extraction.
Experimental comparisons on Twitter datasets indicated that this approach outperformed traditional multimodal sentiment analysis models.

Miao et al. (2025) studied this question.

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This research demonstrates improved accuracy in sentiment analysis using BERT and image features, suggesting enhanced classification effectiveness.