# Comparative Analysis of Engagement, Themes, and Causality of Ukraine-Related Debunks and Disinformation

arXiv: https://arxiv.org/abs/2212.07457 · HTML: https://mlsanity.com/paper/2212.07457/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Dec 2022.

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

- [Breaking Language Barriers with MMTweets: Advancing Cross-Lingual Debunked Narrative Retrieval for Fact-Checking](https://mlsanity.com/paper/2308.05680/) (2023)

## Abstract (arXiv)

This paper compares quantitatively the spread of Ukraine-related disinformation and its corresponding debunks, first by considering re-tweets, replies, and favourites, which demonstrate that despite platform efforts Ukraine-related disinformation is still spreading wider than its debunks. Next, bidirectional post-hoc analysis is carried out using Granger causality tests, impulse response analysis and forecast error variance decomposition, which demonstrate that the spread of debunks has a positive impact on reducing Ukraine-related disinformation eventually, albeit not instantly. Lastly, the paper investigates the dominant themes in Ukraine-related disinformation and their spatiotemporal distribution. With respect to debunks, we also establish that around 18% of fact-checks are debunking claims which have already been fact-checked in another language. The latter finding highlights an opportunity for better collaboration between fact-checkers, so they can benefit from and amplify each other's debunks through translation, citation, and early publication online.