Psychologists pulled off what political pundits and polls failed to do: predict the 2024 presidential election winner.
Before a single ballot was cast in 2024, researchers at the University of Pennsylvania say they already predicted Donald Trump as the winner by tracking how optimistically each candidate explained bad news.
While Trump’s tone grew increasingly upbeat in the final weeks of the campaign, Kamala Harris’s stayed flat. That shift correctly forecast not just that Trump would win, but by how much, according to a new study from Penn’s Positive Psychology Center.
“Starting around October 10 or so, Trump started to get significantly more optimistic,” Martin Seligman, the study’s co-author and a professor of psychology at Penn, told The Post. “By the 27th, it was a very large difference between Harris and Trump.”
The team analyzed 1,389 explanations of negative events — such as war, crime, or economic hardship — from both candidates. Their dataset drew from speeches, interviews, and their only presidential debate, all delivered between early September and October 27.
Each explanation was scored using the CAVE method, or Content Analysis of Verbatim Explanations, a positive psychology technique that analyzes how people explain events in speech or writing. Researchers used it to measure optimism by assessing whether causes were described as temporary, specific, and fixable.
The narrower and solvable the cause, the more “optimistic” the candidate’s message.
Trump referenced more than 1,000 negative issues or events — over four times the number cited by Harris — often blaming outside forces while insisting the problems were fixable, usually by himself, the study found.
Harris, by contrast, described deep, lasting threats with little sense of resolution, Seligman said.
To see whether any other speech patterns could have predicted the results, the researchers also looked at emotional tone, focus on past vs. future and language about control or responsibility. None of them tracked with the outcome. Optimism stood alone.
Seligman’s earlier research found that more optimism predicted the winner in 9 out of the 10 elections between 1948 and 1984.
After that, he advised both political parties on using optimism in their campaigns. But when candidates began scripting fake optimism, he shelved the method.
He only revived it this cycle because Trump’s off-the-cuff style allowed for real-time analysis.
The researchers encrypted their prediction before Election Day and shared it with four outside verifiers, including Wall Street Journal reporters Lara Seligman — daughter of Martin Seligman — and Al Hunt, University of Washington political scientist Dan Chirot, and Hope College psychologist Dave Myers, before publishing the results after the race.
“We’re the only people who predicted a Trump election, as far as I know,” Seligman said.
A separate forecasting model, based on economic conditions and presidential approval ratings, was developed by Cornell University professor Peter Enns and also correctly predicted Trump’s win in all 50 states.
The findings suggest voters respond more favorably to optimistic candidates who present problems as fixable rather than systemic — and that Trump’s tendency to “go off script” gave researchers an authentic glimpse of his true mindset, Seligman said.
“When optimism is genuine, I think there’s a lot of reason to believe that the American public wants optimism and wants hope,” he said. “It speaks to the general optimistic slant of American history.”
Read the full article here
