Fake News

Fake news detection research aims to identify and mitigate the spread of false information online, focusing on improving the accuracy and robustness of detection models. Current research emphasizes the development of multimodal models, often incorporating large language models (LLMs) and techniques like generative adversarial networks (GANs), to analyze text, images, and social context for more comprehensive analysis. This field is crucial for maintaining the integrity of online information ecosystems and protecting individuals and society from the harmful effects of misinformation, with ongoing efforts to improve model explainability and address biases in both data and algorithms.