Fake News Diffusion

Fake news diffusion research aims to understand how misinformation spreads online and develop effective countermeasures. Current research focuses on improving detection models, often employing machine learning techniques like ensemble learning, graph neural networks, and neural temporal point processes, and incorporating social context and user behavior into these models. This work is crucial for mitigating the harmful effects of misinformation on public opinion, democratic processes, and public health, informing the development of more effective interventions and policies.