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Fact-checking has become a key response to disinformation during crises and conflicts, but its role is increasingly contested due to concerns about its effectiveness and its co-optation by different political actors. In polarized, high-choice environments, fact-checking is often embedded within partisan and state-aligned infrastructures, shaping validation and rejection of knowledge claims.

Major platforms constantly claim to fight disinformation and support the fact checking community, but their transparency reports and the empirical evidence from a survey of expert fact checkers across 21 EU countries show a different reality. This study finds that despite commitments made under EU regulations, expert fact checkers remain largely peripheral actors within the existing platform governance framework, with limited insight into how their work influences platform decisions.

We applied a mixed-methods approach with the goal of understanding how Latinx and Asian diaspora communities perceive and experience the spread of misinformation through encrypted messaging apps in the United States. Our study consists of 12 in-depth interviews with leaders of relevant diaspora community organizations and a computer-assisted content analysis of 450,300 messages published on Telegram between July 2020 and December 2021.

This study examined four fact checkers (Snopes, PolitiFact, Logically, and the Australian Associated Press FactCheck) using a data-driven approach. First, we scraped 22,349 fact-checking articles from Snopes and PolitiFact and compared their results and agreement on verdicts. Generally, the two fact checkers agreed with each other, with only one conflicting verdict among 749 matching claims after adjusting minor rating differences.

After his acquisition of Twitter, Elon Musk pledged to overhaul verification and moderation policies. These events sparked fears of a rise in influence of contentious actors—notably from the political right. I investigated whether these actors did receive increased engagement over this period by gathering tweet data for accounts that purchased blue-tick verification before and after the Musk takeover.

Some people share misinformation accidentally, but others do so knowingly. To fully understand the spread of misinformation online, it is important to analyze those who purposely share it. Using a 2022 U.S. survey, we found that 14 percent of respondents reported knowingly sharing misinformation, and that these respondents were more likely to also report support for political violence, a desire to run for office, and warm feelings toward extremists.

We review 100 articles published from 2000 to early 2020 that research aspects of vaccine hesitancy in online communication spaces and identify several gaps in the literature prior to the COVID-19 pandemic. These gaps relate to five areas: disciplinary focus; specific vaccine, condition, or disease focus; stakeholders and implications; research methodology; and geographical coverage.

We analyze the spread of Donald Trump’s tweets that were flagged by Twitter using two intervention strategies—attaching a warning label and blocking engagement with the tweet entirely. We find that while blocking engagement on certain tweets limited their diffusion, messages we examined with warning labels spread further on Twitter than those without labels.

Social media companies have begun to use content-based alerts in their efforts to combat mis- and disinformation, including fact-check corrections and warnings of possible falsity, such as “This claim about election fraud is disputed.” Another harm reduction tool, source alerts, can be effective when a hidden foreign hand is known or suspected.