Abstract

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.

Metadata

publication

Proceedings of the AAAI Conference on Artificial Intelligence 38 (21), 23811 …, 2024

year

2024

publication date

2024/3/24

authors

Mingyu Derek Ma, Alexander K Taylor, Nuan Wen, Yanchen Liu, Po-Nien Kung, Wenna Qin, Shicheng Wen, Azure Zhou, Diyi Yang, Xuezhe Ma, Nanyun Peng, Wei Wang

link

https://ojs.aaai.org/index.php/AAAI/article/view/30573

resource_link

https://ojs.aaai.org/index.php/AAAI/article/view/30573/32735

journal

Proceedings of the AAAI Conference on Artificial Intelligence

volume

38

issue

21

pages

23811-23813