Fake News Detection

Fake news detection aims to automatically identify false or misleading information online, primarily focusing on social media and news articles. Current research emphasizes multimodal approaches, integrating text and image analysis with techniques like large language models (LLMs), generative adversarial networks (GANs), and graph neural networks to leverage both content and social context for improved accuracy. This field is crucial for mitigating the societal harms of misinformation, with ongoing efforts focused on improving model robustness, explainability, and adaptability to diverse languages and data scarcity challenges.