Megan A. Brown
Megan A. Brown is a PhD student at the School of Information at the University of Michigan and a Graduate Research Affiliate at NYU’s Center for Social Media and Politics.
Her research is centered on the online information ecosystem. She studies political bias in algorithmic systems, the effect of platform governance and moderation policies on the spread of political content, and research infrastructure to support computational social science. Formerly, Megan was a Senior Research Engineer at CSMaP, where she collected and maintained large-scale collections of social media and digital trace data for social science research. She received her Bachelor of Arts in Politics with a minor in Middle East & Islamic Studies from New York University in 2019.
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Related Research & News
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News
Text Classification Using a Transformer-Based Model
We're committed to supporting open and accessible science, which includes promoting the creation and use of open-source software, providing high-quality replication materials for our publications, and contributing to existing open-source tools and frameworks. To do so, we created an open-source tool to make using transformers easier and explain how to use it here.
December 8, 2020
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Analysis
How Trump Impacts Harmful Twitter Speech: A Case Study in Three Tweets
We examined three recent tweets from the president and found that harmful speech on Twitter spiked in their immediate aftermath, but soon returned to baseline.
October 22, 2020
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Journal Article
Cross-Platform State Propaganda: Russian Trolls on Twitter and YouTube During the 2016 U.S. Presidential Election
The International Journal of Press/Politics, 2020
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Report
Debate Twitter: Mapping User Reactions to the 2020 Democratic Presidential Primary Debates
As the largest Democratic primary field in modern history continues to narrow, we wanted to examine how the debates drove the conversation online, and specifically how voters changed their opinions over time.
March 3, 2020
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