R.I.P.
๐ป
Ghosted
Information Cascade Prediction under Public Emergencies: A Survey
March 28, 2024 ยท The Cartographer ยท ๐ arXiv.org
"No code URL or promise found in abstract"
"Title-pattern auto-detect: Information Cascade Prediction under Public Emergencies: A Survey"
Evidence collected by the PWNC Scanner
Authors
Qi Zhang, Guang Wang, Li Lin, Kaiwen Xia, Shuai Wang
arXiv ID
2404.01319
Category
cs.SI: Social & Info Networks
Cross-listed
cs.AI,
cs.CY
Citations
2
Venue
arXiv.org
Last Checked
4 days ago
Abstract
With the advent of the era of big data, massive information, expert experience, and high-accuracy models bring great opportunities to the information cascade prediction of public emergencies. However, the involvement of specialist knowledge from various disciplines has resulted in a primarily application-specific focus (e.g., earthquakes, floods, infectious diseases) for information cascade prediction of public emergencies. The lack of a unified prediction framework poses a challenge for classifying intersectional prediction methods across different application fields. This survey paper offers a systematic classification and summary of information cascade modeling, prediction, and application. We aim to help researchers identify cutting-edge research and comprehend models and methods of information cascade prediction under public emergencies. By summarizing open issues and outlining future directions in this field, this paper has the potential to be a valuable resource for researchers conducting further studies on predicting information cascades.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Social & Info Networks
R.I.P.
๐ป
Ghosted
Fake News Detection on Social Media: A Data Mining Perspective
R.I.P.
๐ป
Ghosted
Natural Scales in Geographical Patterns
R.I.P.
๐ป
Ghosted
Representation Learning on Graphs: Methods and Applications
R.I.P.
๐ป
Ghosted
The COVID-19 Social Media Infodemic
R.I.P.
๐ป
Ghosted