Rumour Detection

Rumour detection research aims to automatically identify and classify false or misleading information spreading online, primarily on social media platforms. Current efforts focus on leveraging advanced natural language processing (NLP) techniques, including large language models (LLMs) like BERT and RoBERTa, and graph neural networks (GNNs) to analyze textual content and propagation patterns within social media threads. These models are being enhanced with explainability methods to understand their decision-making processes and improve transparency, and are applied to both veracity prediction and stance classification tasks. The ultimate goal is to develop robust and efficient systems for mitigating the spread of misinformation and its societal impact.