@m_dot_brown

PhD Student @umsi & @UM_MICDE | BA @nyuniversity | formerly engineering @CSMaP_NYU | she/her/hers 🏳️‍🌈

 Ann Arbor, MI
meganbrown.org
Joined June 2014
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70Media
Excited to share a pre-print about web scraping for research! We're happy to receive feedback on how we frame this issue and try to build some paths forward for researchers. w/ Andrew Gruen, @gmaldoff, @SolomonMg, @ZeveSanderson, & @michaelzimmer arxiv.org/abs/2410.23432
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1/ Our new paper in Political Communication asks: does YouTube's algorithm push users into echo chambers, rabbit holes, or radicalization pathways? 🧵
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9/ The broader implication: the concern that recommendation algorithms are radicalization engines appears overstated, at least as of fall 2020. The subtler effect is a platform nudging all users toward ideological moderation while deepening content homogeneity over time.
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10/ Full paper: "Evaluating Echo Chambers, Rabbit Holes, and Radicalization Pathways on YouTube," Political Communication (2026). w/ @JamesBisbee @angelaight @j_a_tucker @Jonathan_Nagler @RichBonneauNYC from @CSMAP_NYU tandfonline.com/doi/full/10.…

Evaluating Echo Chambers, Rabbit Holes, and Radicalization Pathways on YouTube

To what extent does the YouTube recommendation algorithm push users into echo chambers, rabbit holes, or radicalization pathways? Using a novel method to estimate the ideology of YouTube videos and...

tandfonline.com
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Megan A. Brown retweeted
Ross Dahlke 🔑@Ross_DahlkeMar 30
New from me, @yangyunkang @JosephineLukito @j___greenfield @bin_chen19 @m_dot_brown @beccalew: analyzing sales data released from InfoWar's court cases, we find that certain topics and styles (linguistic and auditory) used by Alex Jones on his radio show predict next-day sales
Screenshot of the title page of a journal article in Information, Communication & Society by Ross Dahlke and coauthors. The article is titled “Style and substance on The Alex Jones Show predict InfoWars sales: a multi-modal analysis of a media empire.” The abstract explains that the study combines daily InfoWars sales data from 2016 to 2018 with linguistic, auditory, and topical features from Alex Jones’s radio show and online articles, finding that some styles and topics predict next-day sales.

ALT Screenshot of the title page of a journal article in Information, Communication & Society by Ross Dahlke and coauthors. The article is titled “Style and substance on The Alex Jones Show predict InfoWars sales: a multi-modal analysis of a media empire.” The abstract explains that the study combines daily InfoWars sales data from 2016 to 2018 with linguistic, auditory, and topical features from Alex Jones’s radio show and online articles, finding that some styles and topics predict next-day sales.

Line chart showing daily InfoWars sales in dollars from January 2016 through December 2018. Sales are highly volatile, with frequent spikes, but generally rise from relatively low levels in early 2016 to a higher and more sustained range through 2017 and 2018, often around $100,000 to $300,000 per day, with occasional peaks approaching $1 million.

ALT Line chart showing daily InfoWars sales in dollars from January 2016 through December 2018. Sales are highly volatile, with frequent spikes, but generally rise from relatively low levels in early 2016 to a higher and more sustained range through 2017 and 2018, often around $100,000 to $300,000 per day, with occasional peaks approaching $1 million.

Multi-panel figure showing daily trends in selected themes and styles in Alex Jones radio shows and InfoWars news articles from 2016 to 2018. The left column tracks radio show content including Power, Bio, Achieve, Focus Future, and Money; the right column tracks article content including Power, Achieve, Money, Anger, and Focus Future. Gray daily values are overlaid with smoothed trend lines, showing that some themes shift gradually over time while others remain fairly stable.

ALT Multi-panel figure showing daily trends in selected themes and styles in Alex Jones radio shows and InfoWars news articles from 2016 to 2018. The left column tracks radio show content including Power, Bio, Achieve, Focus Future, and Money; the right column tracks article content including Power, Achieve, Money, Anger, and Focus Future. Gray daily values are overlaid with smoothed trend lines, showing that some themes shift gradually over time while others remain fairly stable.

Multi-panel figure showing daily trends in major topics in Alex Jones radio shows and InfoWars news articles from 2016 to 2018. Radio show panels include Nationalism, Politicians, Show Slogans, Promotions, and Fake News; article panels include Trump, Scientific Discoveries and Controversies, Media and Politics, Attacking Democrats, and Global Conflicts. Smoothed trend lines show modest but noticeable changes over time, including persistent attention to Trump and politics in articles and nationalism and political messaging in radio content.

ALT Multi-panel figure showing daily trends in major topics in Alex Jones radio shows and InfoWars news articles from 2016 to 2018. Radio show panels include Nationalism, Politicians, Show Slogans, Promotions, and Fake News; article panels include Trump, Scientific Discoveries and Controversies, Media and Politics, Attacking Democrats, and Global Conflicts. Smoothed trend lines show modest but noticeable changes over time, including persistent attention to Trump and politics in articles and nationalism and political messaging in radio content.

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Thrilled to have a new article published in @BigDataSoc! 🥳🎉📊 With scraping becoming a more common data collection strategy for internet researchers, we cover the legal, ethical, institutional, and scientific ramifications researchers should consider. doi.org/10.1177/205395172513…

Web scraping for research: Legal, ethical, institutional, and scientific considerations - Megan A...

Scientists across disciplines often use data from the internet to conduct research, generating valuable insights about human behavior. However, as generative ar...

journals.sagepub.com
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Grateful for the collaboration with excellent researchers for this paper @agruen, @gmaldoff, @SolomonMg, @ZeveSanderson, & @michaelzimmer
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✨ New work with wonderful coauthors @JosephineLukito @MG_Macdonald @bin_chen19 @m_dot_brown @stprochas @yangyunkang @j___greenfield @jiyoun_suk @rociozhong @borah
Elections Research Center@ElectionsCenter24 Jul 2025
How do congressional candidates tailor messages across platforms? Research by ERC affiliate @Ross_Dahlke and coauthors finds mobilization strategies vary by platform, not just party, but that only Republicans used alt-tech like Truth Social. Read here: doi.org/10.1177/205630512513…
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📢 Thrilled to share our new article introducing CampaignView—a comprehensive open-source dataset of congressional candidate campaign bios and policy platforms (2018–2022). Paper + data here: campaignview.org & doi.org/10.7910/DVN/JIEAPT 🧵1/4
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Megan A. Brown retweeted
Patrick Y. Wu@PatrickYWu11 Jul 2025
Can large language models (LLMs) fairly annotate data on contentious topics? Our new paper dives into this question—looking at whether LLM-generated labels reflect diverse viewpoints or skew toward majority perspectives. The results are surprisingly nuanced. 🧵
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Megan A. Brown retweeted
Sol Messing
@SolomonMg18 Jun 2025
🧵 NEW PAPER - "Quantifying Narrative Similarity Across Languages" is live at SMR. We combine NLP w pairwise LLM evals to track ideas across media ecosystems and languages. We also figured out a way to eval unsupervised probs on widely understood supervised performance metrics.
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Megan A. Brown retweeted
Kevin Yang
@yang3kc19 May 2025
[New WP] With the closure of major social media APIs and the new data access mandates under DSA, we entered what we call the "post-post-API" era. But have researchers obtained the data they need? Our recent survey (180) + interview (19) study suggests a stark reality. 1/2
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So excited to finally see this out! It was the first paper I started during my postdoc at @CSMaP_NYU
NYU's Center for Social Media, AI, and Politics@CSMAP_NYU17 Mar 2025
It's well known that politicians take more extreme positions during primaries. In @ElectoralStdies, we find this shift is much more likely when incumbents in safe seats face a well-funded primary challenger. 🧵👇 authors.elsevier.com/a/1kn5K…
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