Digital Capitalism and Meta’s Algorithmic Governance: An Empirical Investigation of Instagram’s Fact-Checking Practices

In this study, we collected Instagram posts that contain misinformation in order to understand the fact-checking practices followed by Meta shortly before its decision to cancel its collaboration with fact-checking organizations in 2025. This paper uses the theoretical frameworks of Digital Capitalism and Algorithmic Governance and employs a mixed-method approach. The study’s findings are only meant to offer an empirical reference point before Meta’s new fact-checking policy implementation. The study, which investigated 39 misinformation-related terms, showed that the company used two types of fact-checking ratings (automated and human) that most often labelled posts that contained false news, followed by false and misleading news. Based on the limited collected data, the results indicate some intensification of its fact-checking efforts in 2020 with the emergence of the COVID-19 pandemic, but it greatly reduced the volume of its work in 2022, a few years before its decision to stop working with fact-checkers. The manual thematic categorization of fact-checked posts shows that the most frequent type is related to false claims about harmful or useless vaccines, followed by other claims like harmful or useless facemasks and COVID-19 being fake or unharmful. The implications of the study are discussed in the conclusion.