The study introduces MIDDAG, a system that visualizes how COVID-19 news travels on social media. It provides insights into user and community susceptibility levels and popular opinions raised while spreading information. The researchers built communities among users to understand information flow patterns. They also developed a forecasting capability for propagation. The system demonstrates information propagation details and patterns related to COVID-19 news across social media platforms. A machine-learning-based approach was used to predict the susceptibility level of users and communities. The study also extracted events from each tweet in an information pathway to show how the core ideas of the original article spread.
Publication date: 4 Oct 2023
Project Page: https://arxiv.org/abs/2310.02529v1
Paper: https://arxiv.org/pdf/2310.02529
