Digital platforms have played a significant role in the spread of misinformation during the COVID-19 pandemic. Misinformation related to the pandemic can have consequences for public health and for compliance with government measures.

Therefore, fact-checking organizations have investigated stories that potentially spread misinformation and published their findings online, aiming to curb the negative impact of misinformation on society.

These fact-checked stories are also collectively published in fact-checking databases, which form new overarching infrastructures for fact-checking.

This study aims to conceptualize fact-checking as overarching digital infrastructures by comparing two such infrastructures, which differ technically and economically:

Poynter and Google Fact-Check Explorer (hereafter referred to as 'Google').

The Poynter infrastructure comes from the #CoronaVirusFacts Alliance of the IFCN (International Fact-Checking Network), which operates under the Poynter Institute, a non-profit organization, while the Google infrastructure is provided by a for-profit company.

The study seeks to examine overlaps and differences, thereby identifying biases in the two infrastructures.

First, it looks at the number of overlapping stories and whether they match in the assessments used.

When comparing the two infrastructures, the authors closely examine the following parameters:

Who debunks the misinformation?
Where was the misinformation published?
Who published the misinformation?
What content was published?

The authors have established a method for each of these questions, which can be used by other researchers analyzing similar data.

The case study concludes, among other things, that fact-checking, as digital infrastructures with downstream effects on society when used by a diverse set of stakeholders (e.g., the public, news media, researchers), is biased by favoring certain types of content, platforms, and continents over others.