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Information Cascade Prediction under Public Emergencies: A Survey

arXiv 2404.01319 ↗First posted 28 Mar 2024cs.SI cs.AI cs.CYcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 227 references that are in the map. First posted on arXiv 28 Mar 2024.

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References · 19

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7 more
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