PennMAP
Penn Media Accountability Project
“Half the Truth is often a great Lie.”
– Benjamin Franklin
PennMAP is an interdisciplinary, nonpartisan research project of the Computational Social Science Lab at the University of Pennsylvania dedicated to enhancing media transparency and accountability at the scale of the entire information ecosystem.
Misinformation in media is believed to have harmful effects on public opinion, political polarization, and ultimately democratic decision making. And yet, much remains unknown regarding the prevalence of misinformation and its effects on society.
To address this problem, PennMAP is building technology to detect patterns of bias and misinformation in media from across the political spectrum and spanning television, radio, social media, and the broader web. We will also track consumption of information via television, desktop computers, and mobile devices, as well as its effects on individual and collective beliefs and understanding.
In collaboration with our data partners, we are also building a scalable data infrastructure to ingest, process, and analyze tens of terabytes of television, radio, and web content, as well as representative panels of roughly 100,000 media consumers over several years. While our initial focus is on the U.S., our hope is to scale this infrastructure to eventually cover other countries and languages other than English.
We will share our insights through publications and interactive data visualizations, and will work with various stakeholders—including journalists, policy makers, and industry partners—to implement solutions. Aside from powering our own research, our infrastructure will support other research teams, thereby accelerating the pace of knowledge accumulation and enhancing its reliability.
ABOVE: Evaluating the fake news problem at the scale of the information ecosystem
Selections from the 2020 paper “Evaluating the fake news problem at the scale of the information ecosystem,” coauthored by Lab Director Duncan Watts, Baird Howland, and David Rothschild. With data spanning from January 2016 to December 2018, the piece examines the news ecosystem on a large scale to determine the prevalence of fake news.
Read the full paper here.
PEOPLE
Duncan Watts
—
Stevens University Professor & twenty-third Penn Integrates Knowledge Professor
Homa Hosseinmardi
—
Research Scientist
James Houghton
—
Research Scientist
Amir Ghasemian
—
Affiliate Research Scientist
David Rothschild
—
Affiliate Research Scientist
Samar Haider
—
Ph.D. Researcher
Baird Howland
—
Ph.D. Researcher
Bryan Li
—
Ph.D. Researcher
Keith Golden
—
Graduate Student Researcher
Kailun Li
—
Graduate Student Researcher
Tai Nguyen
—
Graduate Student Researcher
Xi (Robby) Qiu
—
Graduate Student Researcher
Vivienne Chen
—
Undergraduate Student Researcher
Yue (Flora) Chen
—
Undergraduate Student Researcher
Josh Ludan
—
Undergraduate Student Researcher
FEATURED PUBLICATIONS
Reducing opinion polarization: Effects of exposure to similar people with differing political views Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 52, 2021.
Success stories cause false beliefs about success Journal Article
In: Judgment and Decision Making, vol. 16, no. 6, pp. 1439-1463, 2021, ISSN: 1930-2975.
Examining the consumption of radical content on YouTube Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 32, 2021.
Research note: Examining potential bias in large-scale censored data Journal Article
In: Harvard Kennedy School (HKS) Misinformation Review, 2021.
Measuring the news and its impact on democracy Journal Article
In: Proceedings of the National Academy of Sciences, vol. 118, no. 15, 2021.
Evaluating the fake news problem at the scale of the information ecosystem Journal Article
In: Science Advances, vol. 6, no. 14, pp. eaay3539, 2020.
Understanding Cyberbullying on Instagram and Ask.fm via Social Role Detection Journal Article
In: Companion Proceedings of The 2019 World Wide Web Conference, pp. 183-188, 2019.
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