The False COVID-19 Narratives That Keep Being Debunked: A Spatiotemporal Analysis

TL;DR

The paper addresses the problem of a global COVID-19 misinformation infodemic that leads to repetitive debunking across languages and countries. It analyzes the IFCN CoronaVirusFacts Alliance dataset (10,381 debunks) using a cross-lingual retrieval pipeline (BM25 + RoBERTa) to identify duplicate debunks and examines their spatiotemporal patterns across countries, platforms, and content modalities. Key findings show that about 10% of debunks have prior duplicates, with India and the US driving many recurring narratives, and that general medical advice claims dominate duplicate debunks; many duplicates lack same-language counterparts, underscoring the need for multilingual search in fact-checking pipelines. The study contributes quantitative evidence of cross-language/narrative propagation, highlights platform- and modality-shifts in duplicates, and advocates for multilingual debunk search tools and platform-scale adoption to optimize fact-checker resource use and reduce redundant work. These insights can enhance early warning, cross-lingual retrieval, and moderation strategies in digital information ecosystems.

Abstract

The onset of the COVID-19 pandemic led to a global infodemic that has brought unprecedented challenges for citizens, media, and fact-checkers worldwide. To address this challenge, over a hundred fact-checking initiatives worldwide have been monitoring the information space in their countries and publishing regular debunks of viral false COVID-19 narratives. This study examines the database of the CoronaVirusFacts Alliance, which contains 10,381 debunks related to COVID-19 published in multiple languages by different fact-checking organisations. Our spatiotemporal analysis reveals that similar or nearly duplicate false COVID-19 narratives have been spreading in multiple modalities and on various social media platforms in different countries, sometimes as much as several months after the first debunk of that narrative has been published by an International Fact-checking Network (IFCN) fact-checker. We also find that misinformation involving general medical advice has spread across multiple countries and hence has the highest proportion of false COVID-19 narratives that keep being debunked. Furthermore, as manual fact-checking is an onerous task in itself, therefore the need to repeatedly debunk the same narrative in different countries is leading, over time, to a significant waste of fact-checker resources. To this end, we propose the idea of including a multilingual debunk search tool in the fact-checking pipeline, in addition to recommending strongly that social media platforms need to adopt the same technology at scale, so as to make the best use of scarce fact-checker resources.

Figures (11)

• Figure 1: Left: Pie chart distribution for top 10 countries where the claims already debunked were spreading. Right: Pie chart distribution for top 10 fact-checking organisations that published fact-checking articles about the claims that were debunked in the past.
• Figure 2: Histogram plot for days difference between query claim debunks and duplicate claim debunks. (Bin set at an interval of 1 week).
• Figure 3: The movement of similar false claims between different country pairs. The bar chart on the left shows the top 10 counts of cases where both the countries are same and the bar chart on the right depicts the top 10 cases where both countries are different.
• Figure 4: Left: Transition in social media platforms. Right: Transition between modality of content.
• Figure 5: Top 10 count of cases showing the difference in the language used in the fact-checking articles for both the query claim debunk and the duplicate claim debunk. ISO-39 language code is used to denote the language.