Publication date: 
Irene V. Pasquetto
Briony Swire Thompson
Michelle A. Amazeen
Fabricio Benevenuto
Nadia M. Brashier
Robert M. Bond
Lia C. Bozarth
Ceren Budak
Ullrich K. H. Ecker
Lisa K. Fazio
Emilio Ferrara
Andrew J. Flanagin
Alessandro Flammini
Deen Freelon
Nir Grinberg
Ralph Hertwig
Kathleen Hall Jamieson
Kenny Joseph
Jason J. Jones
R. Kelly Garrett
Daniel Kreiss
Shannon McGregor
Jasmine McNealy
Drew Margolin
Alice Marwick
Filippo Menczer
Miriam J. Metzger
Seungahn Nah
Stephan Lewandowsky
Philipp Lorenz-Spreen
Pablo Ortellado
Gordon Pennycook
Ethan Porter
David G. Rand
Ronald Robertson
Francesca Tripodi
Soroush Vosoughi
Chris Vargo
Onur Varul
Brian E. Weeks
John Wihbey
Thomas J. Wood
Kai-Cheng Yang

Social media platforms rarely provide data to misinformation researchers. This is problematic as platforms play a major role in the diffusion and amplification of mis- and disinformation narratives. Scientists are often left working with partial or biased data and must rush to archive relevant data as soon as it appears on the platforms, before it is suddenly and permanently removed by deplatforming operations.

Publication date: 
Briony Swire Thompson
Joe DeGutis
David Lazer

One of the most concerning notions for science communicators, fact-checkers, and advocates of truth, is the backfire effect; this is when a correction leads to an individual increasing their belief in the very misconception the correction is aiming to rectify.

Publication date: 
Sarah Shugars

Agent-based models present an ideal tool for interrogating the dynamics of communication and exchange. Such models allow individual aspects of human interaction to be isolated and controlled in a way that sheds new insight into complex behavioral phenomena. This approach is particularly valuable in settings beset by confounding factors and mixed empirical evidence.

Publication date: 
Jason Radford
Kenny Joseph

Research at the intersection of machine learning and the social sciences has provided critical new insights into social behavior. At the same time, a variety of issues have been identified with the machine learning models used to analyze social data.

machine learning
computational social science
machine learning and social science
Publication date: 
Briony Swire Thompson
David Lazer

The internet has become a popular resource to learn about health and to investigate one's own health condition. However, given the large amount of inaccurate information online, people can easily become misinformed. Individuals have always obtained information from outside the formal health care system, so how has the internet changed people's engagement with health information?

fake news
social media
Publication date: 
Kenny Joseph
Briony Swire Thompson
Hannah Masuga
Matthew A. Baum
David Lazer

Using both survey- and platform-based measures of support, we study how polarization manifests for 4,313 of President Donald Trump’s tweets since he was inaugurated in 2017. We find high levels of polarization in response to Trump’s tweets. However, after controlling for mean differences, we surprisingly find a high degree of agreement across partisan lines across both survey and platform-based measures.

Publication date: 
Sarah Shugars
Nick Beauchamp

Individuals acquire increasingly more of their political information from social media, and ever more of that online time is spent in interpersonal, peer-to-peer communication and conversation. Yet, many of these conversations can be either acrimoniously unpleasant or pleasantly uninformative. Why do we seek out and engage in these interactions? Who do people choose to argue with, and what brings them back to repeated exchanges?

social media
interpersonal communication
natural language processing

Publications by type

Journal Article