Various Rumour Propagation Behaviour

Research on rumour propagation behavior focuses on understanding how misinformation spreads online and developing effective detection and mitigation strategies. Current efforts utilize various machine learning models, including large language models and graph-based approaches, to analyze textual content, user interactions, and the temporal dynamics of rumour spread. These methods aim to improve the accuracy and speed of rumour detection, often incorporating explainability techniques to enhance transparency and understanding. The ultimate goal is to develop robust tools to combat the harmful effects of online misinformation and protect the integrity of information ecosystems.