MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways
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.
Cite
Text
Ma et al. "MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways." AAAI Conference on Artificial Intelligence, 2024. doi:10.1609/AAAI.V38I21.30573Markdown
[Ma et al. "MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways." AAAI Conference on Artificial Intelligence, 2024.](https://mlanthology.org/aaai/2024/ma2024aaai-middag/) doi:10.1609/AAAI.V38I21.30573BibTeX
@inproceedings{ma2024aaai-middag,
title = {{MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways}},
author = {Ma, Mingyu Derek and Taylor, Alexander K. and Wen, Nuan and Liu, Yanchen and Kung, Po-Nien and Qin, Wenna and Wen, Shicheng and Zhou, Azure and Yang, Diyi and Ma, Xuezhe and Peng, Nanyun and Wang, Wei},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2024},
pages = {23811-23813},
doi = {10.1609/AAAI.V38I21.30573},
url = {https://mlanthology.org/aaai/2024/ma2024aaai-middag/}
}