Paper
8 November 2023 Image-text fusion sentiment analysis with textual attention
Hong Zhang, Wen-Yuan Zhang, Kun Jiang, En-Xiang Yang
Author Affiliations +
Proceedings Volume 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023); 1292326 (2023) https://doi.org/10.1117/12.3011820
Event: 3rd International Conference on Artificial Intelligence, Virtual Reality and Visualization (AIVRV 2023), 2023, Chongqing, China
Abstract
With the development of information technology and big data, large amount of multimodal data with opinion biases has exploded. Compared to unimodal data, multimodal data can accurately identify users' emotional tendencies and enrich emotional attitudes from a variety of perspectives. To effectively identify the consistency of sentiment representations between image and text semantics, as well as the variability in the degree of contribution in sentiment analysis, an imagetext fusion sentiment analysis method based on text attention is proposed. The method constructs attention-based models for extracting text and images' features, emphasizes the words containing sentiment information, and builds a sentiment classification model using multimodal feature fusion. Experimental results show fusion method proposed has achieved better performance in both accuracy and F1 values compared with baseline models.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hong Zhang, Wen-Yuan Zhang, Kun Jiang, and En-Xiang Yang "Image-text fusion sentiment analysis with textual attention", Proc. SPIE 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023), 1292326 (8 November 2023); https://doi.org/10.1117/12.3011820
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KEYWORDS
Feature fusion

Image fusion

Data modeling

Feature extraction

Image classification

Data fusion

Image analysis

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