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.

在大数据时代，信息蔓延的预测在大规模信息、专家经验和高精度模型的帮助下带来了巨大机遇。然而，不同学科的专业知识参与导致信息蔓延预测主要专注于特定应用领域（如地震、洪水、传染病）。缺乏统一的预测框架为不同应用领域的交叉预测方法的分类带来了挑战。本文提供了信息蔓延建模、预测和应用的系统分类和总结。我们旨在帮助研究人员识别前沿研究，了解公共紧急情况下信息蔓延预测的模型和方法。通过总结目前存在的问题并概述未来研究方向，本文有潜力成为研究人员进一步研究信息蔓延预测的宝贵资源。