Research
CSMaP is a leading academic research institute studying the ever-shifting online environment at scale. We publish peer-reviewed research in top academic journals, produce rigorous reports and analyses on policy relevant topics, and develop open source tools and methods to support the broader scholarly community.
Academic Research
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Journal Article
The Diffusion and Reach of (Mis)Information on Facebook During the U.S. 2020 Election
Sociological Science, 2024
Social media creates the possibility for rapid, viral spread of content, but how many posts actually reach millions? And is misinformation special in how it propagates? We answer these questions by analyzing the virality of and exposure to information on Facebook during the U.S. 2020 presidential election. We examine the diffusion trees of the approximately 1 B posts that were re-shared at least once by U.S.-based adults from July 1, 2020, to February 1, 2021. We differentiate misinformation from non-misinformation posts to show that (1) misinformation diffused more slowly, relying on a small number of active users that spread misinformation via long chains of peer-to-peer diffusion that reached millions; non-misinformation spread primarily through one-to-many affordances (mainly, Pages); (2) the relative importance of peer-to-peer spread for misinformation was likely due to an enforcement gap in content moderation policies designed to target mostly Pages and Groups; and (3) periods of aggressive content moderation proximate to the election coincide with dramatic drops in the spread and reach of misinformation and (to a lesser extent) political content.
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Journal Article
Reports & Analysis
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Analysis
Who Has a Policy that Would Benefit You? More Voters Say Trump.
National survey data from the 2016, 2020, and 2024 elections shed light on how candidates' campaign strategies impact voter policy recall.
November 2, 2024
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Analysis
Reducing Exposure To Misinformation: Evidence from WhatsApp in Brazil
Deactivating multimedia on WhatsApp in Brazil consistently reduced exposure to online misinformation during the pre-election weeks in 2022, but did not impact whether false news was believed, or reduce polarization.
August 16, 2024
Data Collections & Tools
As part of our project to construct comprehensive data sets and to empirically test hypotheses related to social media and politics, we have developed a suite of open-source tools and modeling processes.