Megan A. Brown
Megan A. Brown is a senior research engineer and research scientist at NYU’s Center for Social Media and Politics. As research engineer, Brown collects and maintains large-scale collections of social media and digital trace data for the purposes of social science research. In her research endeavors, she studies cross-platform media manipulation, political bias in algorithmic systems, and the effect of platform governance and moderation policies on the spread of political content.
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Related Research & News
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Commentary
The Problem with TikTok’s New Researcher API is Not TikTok
While TikTok’s Researcher API is a promising step in the right direction, mandated data requirements are paramount for ensuring that these lines of research continue.
March 1, 2023
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Analysis
Echo Chambers, Rabbit Holes, and Ideological Bias: How YouTube Recommends Content to Real Users
We find that YouTube’s recommendation algorithm does not lead the vast majority of users down extremist rabbit holes, although it does push users into increasingly narrow ideological ranges of content in what we might call evidence of a (very) mild ideological echo chamber.
October 13, 2022
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Journal Article
Election Fraud, YouTube, and Public Perception of the Legitimacy of President Biden
Journal of Online Trust and Safety, 2022
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Analysis
Republicans Are Increasingly Sharing Misinformation
Republican candidates have dramatically increased how much they share from unreliable sources in just two years.
August 29, 2022
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Working Paper
Echo Chambers, Rabbit Holes, and Algorithmic Bias: How YouTube Recommends Content to Real Users
Working Paper, May 2022
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Working Paper
Estimating the Ideology of Political YouTube Videos
Working Paper, May 2022
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Working Paper
To Moderate, Or Not to Moderate: Strategic Domain Sharing by Congressional Campaigns
Working Paper, April 2022
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Analysis
Gender-Based Online Violence Spikes After Prominent Media Attacks
Our research finds that after a prominent male media personality targets a female journalist, the prevalence of hateful speech targeting those journalists increases in the immediate aftermath, often taking days to decrease.
January 26, 2022
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Analysis
Twitter Banned Marjorie Taylor Greene. That May Not Hurt Her Much.
She’s gaining followers and ‘likes’ on other social media platforms, our research finds.
January 14, 2022
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Analysis
Trendless Fluctuation? How Twitter’s Ethiopia Interventions May (Not) Have Worked
Twitter’s decision to deactivate trending topics in Ethiopia did not reduce the volume or toxicity of tweets about the civil war.
January 11, 2022
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Working Paper
Network Embedding Methods for Large Networks in Political Science
Working Paper, November 2021
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Analysis
Twitter Amplifies Conservative Politicians. Is it Because Users Mock Them?
Our research suggests conservative politicians are ‘ratioed’ more often, which may explain why they’re in your timeline.
October 27, 2021
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Journal Article
SARS-CoV-2 RNA Concentrations in Wastewater Foreshadow Dynamics and Clinical Presentation of New COVID-19 Cases
Science of the Total Environment, 2022
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Journal Article
Twitter Flagged Donald Trump’s Tweets with Election Misinformation: They Continued to Spread Both On and Off the Platform
Harvard Kennedy School (HKS) Misinformation Review, 2021
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Analysis
Do Twitter Warning Labels Work?
Twitter put warning labels on hundreds of thousands of tweets. Without a hard block, tweets continue to spread — especially tweets by President Trump.
December 9, 2020
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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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Data Report
Debate Twitter: Mapping User Reactions to the 2020 Democratic Presidential Primary Debates
Data Report, NYU's Center for Social Media and Politics, 2020