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

Autor:	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
Rok vydání:	2023
Předmět:	Computer Science - Social and Information Networks Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction
Druh dokumentu:	Working Paper
Popis:	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. Comment: To appear at AAAI'24. System demo video and more info: info-pathways.github.io
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2310.02529 Zobrazit plný text záznamu View this record from Arxiv