# Information Cascade Prediction under Public Emergencies: A Survey

arXiv: https://arxiv.org/abs/2404.01319 · HTML: https://mlsanity.com/paper/2404.01319/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 19 of its 227 references that are in the map.
- First posted on arXiv 28 Mar 2024.

## Builds on (most cited first, 19 of 19)

- [StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation](https://mlsanity.com/paper/1711.09020/) (2017)
- [Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning](https://mlsanity.com/paper/1612.01887/) (2016)
- [Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model](https://mlsanity.com/paper/1511.01644/) (2015)
- [Constructing Narrative Event Evolutionary Graph for Script Event Prediction](https://mlsanity.com/paper/1805.05081/) (2018)
- [Can Cascades be Predicted?](https://mlsanity.com/paper/1403.4608/) (2014)
- [Detecting natural disasters, damage, and incidents in the wild](https://mlsanity.com/paper/2008.09188/) (2020)
- [A Bayesian approach for predicting the popularity of tweets](https://mlsanity.com/paper/1304.6777/) (2013)
- [A Mixture Model for Learning Multi-Sense Word Embeddings](https://mlsanity.com/paper/1706.05111/) (2017)
- [Unsupervised Detection of Sub-events in Large Scale Disasters](https://mlsanity.com/paper/1912.13332/) (2019)
- [Identifying and Analyzing Cryptocurrency Manipulations in Social Media](https://mlsanity.com/paper/1902.03110/) (2019)
- [Localizing and Quantifying Damage in Social Media Images](https://mlsanity.com/paper/1806.07378/) (2018)
- [On Identifying Hashtags in Disaster Twitter Data](https://mlsanity.com/paper/2001.01323/) (2020)
- [Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models](https://mlsanity.com/paper/1711.08493/) (2017)
- [Deep Learning for Real-Time Crime Forecasting and its Ternarization](https://mlsanity.com/paper/1711.08833/) (2017)
- [Wayeb: a Tool for Complex Event Forecasting](https://mlsanity.com/paper/1901.01826/) (2018)
- [Event Forecasting with Pattern Markov Chains](https://mlsanity.com/paper/1804.10388/) (2018)
- [A Deep Learning Approach for Tweet Classification and Rescue Scheduling for Effective Disaster Management](https://mlsanity.com/paper/1908.01456/) (2019)
- [Weakly-supervised Fine-grained Event Recognition on Social Media Texts for Disaster Management](https://mlsanity.com/paper/2010.01683/) (2020)
- [Popularity Prediction in Microblogging Network: A Case Study on Sina Weibo](https://mlsanity.com/paper/1304.4324/) (2013)

## 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.