MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways

• URL: http://arxiv.org/abs/2310.02529v2
• Date: Tue, 20 Feb 2024 19:48:15 GMT
• Title: MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways
• 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
• Abstract summary: We present MIDDAG, an intuitive, interactive system that visualizes the information propagation paths on social media triggered by COVID-19-related news articles. We construct communities among users and develop the propagation forecasting capability, enabling tracing and understanding of how information is disseminated at a higher level.
• Score: 114.42360191723469
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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