MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways - Ma, Mingyu Derek; Taylor, Alexander K.; Wen, Nuan; Liu, Yanchen; Kung, Po-Nien; Qin, Wenna; Wen, Shicheng; Zhou, Azure; Yang, Diyi; Ma, Xuezhe; Peng, Nanyun; Wang, Wei (Proceedings of the AAAI Conference on Artificial Intelligence, 2024)
We present MIDDAG, an intuitive, interactive system that visualizes the information propagation paths on social media triggered by COVID-19-related news articles accompanied by comprehensive insights including user/community susceptibility level, as well as events and popular opinions raised by the crowd while propagating the information. Besides discovering information flow patterns among users, we construct communities among users and develop the propagation forecasting capability, enabling tracing and understanding of how information is disseminated at a higher level. A demo video and more are available at https://info-pathways.github.io.