# Detecting fake news for the new coronavirus by reasoning on the Covid-19 ontology

arXiv: https://arxiv.org/abs/2004.12330 · HTML: https://mlsanity.com/paper/2004.12330/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Apr 2020.

## Built on by (most cited first, 1 of 1)

- [Memory-First Fact-Checking: A Knowledge-Graph-Grounded Multi-Agent System for Misinformation Detection](https://mlsanity.com/paper/2608.29617/) (2026)

## Abstract (arXiv)

In the context of the Covid-19 pandemic, many were quick to spread deceptive information. I investigate here how reasoning in Description Logics (DLs) can detect inconsistencies between trusted medical sources and not trusted ones. The not-trusted information comes in natural language (e.g. "Covid-19 affects only the elderly"). To automatically convert into DLs, I used the FRED converter. Reasoning in Description Logics is then performed with the Racer tool.