  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.
