Multimodal false information detection method based on Text-CNN and SE module.

ABSTRACT: False information detection can detect false information in social media and reduce its negative impact on society. With the development of multimedia, the multimodal content contained in false information is increasing, so it is important to use multimodal features to detect false information. This paper mainly uses information from two modalities, text and image. The features extracted by the backbone network are not further processed in the previous work, and the problems of noise and information loss in the process of fusing multimodal features are ignored. This paper proposes a false information detection method based on Text-CNN and SE modules. We use Text-CNN to process the text and image features extracted by BERT and Swin-transformer to enhance the quality of the features. In addi

SUBMITTER: Liang Y 

PROVIDER: S-EPMC9683577 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature