A fake image which seems to show CNN broadcasting US election results from the state of Texas ahead of election day has been circulating on social media.
But the broadcaster has confirmed the graphic, which appears to be a “key race alert” showing Kamala Harris six points ahead of Donald Trump from 2.1 million votes, is not real.
Multiple social media accounts on X (formerly Twitter) and Facebook have been sharing the image since the early hours of 3 November (UK time), with captions saying: “Are they planning on stealing Texas and it’s 40 electoral votes? [sic].” It has also been shared on Instagram and Threads.
The image also includes a progress bar in the right-hand corner, suggesting a percentage of votes have already been counted, and states that “Polls closed 9:00 ET” in the left-hand corner.
Although early voting opened in Texas from 21 October to 1 November, the image has been circulating days before election day polls close at 7pm CST (which would be 8pm ET, not 9pm) in the state on 5 November, and no results—including these early votes—have yet been announced.
And the mathematics within the image also does not add up. Although the graphic claims that Ms Harris is 121,408 votes ahead of Mr Trump, the difference between the votes attributed to them is actually 131,408.
Emily Kuhn, CNN’s senior vice president of communications, told Full Fact via email: “This image is completely fabricated and manipulated and it never aired on any CNN platform.”
The result of the US presidential election won’t be confirmed until after the last of the polls close at 1am EST (6am GMT) on 6 November. Polls in Texas are open on election day from 7am to 7pm CST, and from 7am Mountain Time in El Paso. Early voting results for Texas are often released just after polls close at 7pm.
Full Fact has debunked a number of misleading social media posts throughout the election campaign, including faked CNN headlines, edited photos and likely AI-created images.
We have written a number of guides to help, including on how to spot misleading images and videos. We’ve also created a toolkit to help identify misinformation, and written about how to spot AI-generated images and videos.