# Assessing the risks of "infodemics" in response to COVID-19 epidemics

arXiv: https://arxiv.org/abs/2004.03997 · HTML: https://mlsanity.com/paper/2004.03997/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Apr 2020.

## Built on by (most cited first, 14 of 14)

- [Sentiment Analysis and Topic Modeling for COVID-19 Vaccine Discussions](https://mlsanity.com/paper/2111.04415/) (2021)
- [Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Language](https://mlsanity.com/paper/2109.07909/) (2021)
- [TrumorGPT: Graph-Based Retrieval-Augmented Large Language Model for Fact-Checking](https://mlsanity.com/paper/2505.07891/) (2025)
- [Analyzing the Strategy of Propaganda using Inverse Reinforcement Learning: Evidence from the 2022 Russian Invasion of Ukraine](https://mlsanity.com/paper/2307.12788/) (2023)
- [The Evolution of Rumors on a Closed Platform during COVID-19](https://mlsanity.com/paper/2104.13816/) (2021)
- [Survey of Generative Methods for Social Media Analysis](https://mlsanity.com/paper/2112.07041/) (2021)
- [GraphSL: An Open-Source Library for Graph Source Localization Approaches and Benchmark Datasets](https://mlsanity.com/paper/2405.03724/) (2024)
- [Harm in AI-Driven Societies: An Audit of Toxicity Adoption on Chirper.ai](https://mlsanity.com/paper/2601.01090/) (2026)
- [A Multi-Branch Feature Fusion Approach for Health Misinformation Detection and Propagation](https://mlsanity.com/paper/2609.00403/) (2026)
- [Detecting Propaganda on the Sentence Level during the COVID-19 Pandemic](https://mlsanity.com/paper/2108.12269/) (2021)
- [An Overview of Healthcare Data Analytics With Applications to the COVID-19 Pandemic](https://mlsanity.com/paper/2111.14623/) (2021)
- [User Experience Design for Automatic Credibility Assessment of News Content About COVID-19](https://mlsanity.com/paper/2204.13943/) (2022)
- [Adversarial Botometer: Adversarial Analysis for Social Bot Detection](https://mlsanity.com/paper/2405.02016/) (2024)
- [Bot Meets Shortcut: How Can LLMs Aid in Handling Unknown Invariance OOD Scenarios?](https://mlsanity.com/paper/2511.08455/) (2025)

## Abstract (arXiv)

Our society is built on a complex web of interdependencies whose effects become manifest during extraordinary events such as the COVID-19 pandemic, with shocks in one system propagating to the others to an exceptional extent. We analyzed more than 100 millions Twitter messages posted worldwide in 64 languages during the epidemic emergency due to SARS-CoV-2 and classified the reliability of news diffused. We found that waves of unreliable and low-quality information anticipate the epidemic ones, exposing entire countries to irrational social behavior and serious threats for public health. When the epidemics hit the same area, reliable information is quickly inoculated, like antibodies, and the system shifts focus towards certified informational sources. Contrary to mainstream beliefs, we show that human response to falsehood exhibits early-warning signals that might be mitigated with adequate communication strategies.