The 2024 U.S. presidential debates kicked off June 27, with President Joe Biden and former President Donald Trump sharing the stage for the first time in four years. Duncan Watts, a computational social scientist from the University of Pennsylvania, considers this an ideal moment to test a tool his lab has been developing during the last six months: the Media Bias Detector.

“The debates offer a real-time, high-stakes environment to observe and analyze how media outlets present and potentially skew the same event,” says Watts, a Penn Integrates Knowledge Professor with appointments in the Annenberg School for Communication, School of Engineering and Applied Science, and Wharton School. “We wanted to equip regular people with a powerful, useful resource to better understand how major events, like this election, are being reported on.”

Researchers at the Computational Social Science Lab (CSSLab) at the University of Pennsylvania, led by Stevens University Professor Duncan Watts, study Americans’ news consumption. In a new article in Nature, Watts, along with David Rothschild of Microsoft Research (Wharton Ph.D. ‘11 and PI in the CSSLab), Ceren Budak of the University of Michigan, Brendan Nyhan of Dartmouth College, and Annenberg alumnus Emily Thorson (Ph.D. ’13) of Syracuse University, review years of behavioral science research on exposure to false and radical content online and find that exposure to harmful and false information on social media is minimal to all but the most extreme people, despite a media narrative that claims the opposite.

Every day, American news outlets collectively publish thousands of articles. In 2016, according to The Atlantic, The Washington Post published 500 pieces of content per day; The New York Times and The Wall Street Journal more than 200. “We’re all consumers of the media,” says Duncan Watts, Stevens University Professor in Computer and Information Science. “We’re all influenced by what we consume there, and by what we do not consume there.”

The Computational Social Sciences Lab’s (CSSLab) new dashboard, Mapping the (Political) Information Ecosystem, is a set of four data visualizations that highlight Americans’ media consumption habits, with a focus on echo chambers and the news. This is the second of a series of dashboards launched by the CSSLab, as part of its PennMAP (Penn Media Accountability) project, and focuses on expanding knowledge on the media by translating research papers into interactive, digestible content.

CAMBRIDGE, Mass., May 30, 2024 – Since the rollout of the COVID-19 vaccine in 2021, fake news on social media has been widely blamed for low vaccine uptake in the United States — but research by MIT Sloan School of Management PhD candidate Jennifer Allen and Professor David Rand finds that the blame lies elsewhere. 

Homa Hosseinmardi and Sam Wolken of the Computational Social Science Lab (CSSLab) were recently invited to speak at the Political and Information Networks Workshop on April 25-26. This workshop was organized by the Center for Information Networks and Democracy (CIND), a new lab under the Annenberg School of Communication. CIND studies how communication networks in the digital era play a role in democratic processes, and its research areas include Information Ecosystems and Political Segregation (or Partisan Segregation).

On the weekend of March 2-3, 2024, the landing page of the New York Times was dominated by coverage of their poll showing voter concern over President Biden’s age. There was a lot of concern among Democrats about the methods of the poll, especially around the low response rate and leading questions. But as a team of researchers who study both survey methods and mainstream media, we are not surprised that people are telling pollsters they are worried about Biden’s age. Why wouldn’t they? The mainstream media has been telling them to be worried about precisely this issue for months.