Megan A. Brown

Megan A. Brown

she/her

PhD Student in Information and Scientific Computing

Publications

You can also find my articles on my Google Scholar profile.

Journal Articles

Quantifying Narrative Similarity Across Languages

Published in Sociological Methods & Research, 2025

How can one understand the spread of ideas across text data? This is a key measurement problem in sociological inquiry, from the study of how interest groups shape media discourse… Read more

Recommended citation: Waight, H., Messing, S., Shirikov, A., Roberts, M. E., Nagler, J., Greenfield, J., Brown, M. A., Aslett, K., & Tucker, J. A. (2025). Quantifying Narrative Similarity Across Languages. Sociological Methods & Research, 0(0). https://doi.org/10.1177/00491241251340080
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To moderate, or not to moderate: Strategic domain sharing by congressional campaigns

Published in Electoral Studies, 2025

We test whether candidates move to the extremes before a primary but then return to the center for the general election to appeal to the different preferences of each electorate… Read more

Recommended citation: Macdonald, M., Brown, M. A., Tucker, J. A., & Nagler, J. (2025). To moderate, or not to moderate: Strategic domain sharing by congressional campaigns. Electoral Studies, 95, 102907.
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Candidates Be Posting: Multi-Platform Strategies and Partisan Preferences in the 2022 U.S. Midterm Elections

Published in Social Media + Society, 2025

We test whether candidates move to the extremes before a primary but then return to the center for the general election to appeal to the different preferences of each electorate… Read more

Recommended citation: Lukito, J., Macdonald, M., Chen, B., Brown, M. A., Prochaska, S., Yang, Y., Greenfield, J., Suk, J., Zhong, W., Dahlke, R., & Borah, P. (2025). Candidates Be Posting: Multi-Platform Strategies and Partisan Preferences in the 2022 U.S. Midterm Elections. Social Media + Society, 11(2). https://doi.org/10.1177/20563051251337541 (Original work published 2025)
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Making academia suck less: Supporting early career researchers studying harmful content online through a feminist ethics of care

Published in New Media & Society, 2024

Early career researchers (ECR) in communication and media research face increasing problems and stressors due to systemic challenges in academia… Read more

Recommended citation: Brown, M. A., Lukito, J., Pruden, M. L., & Riedl, M. J. (2024). Making academia suck less: Supporting early career researchers studying harmful content online through a feminist ethics of care. New Media & Society, 0(0). https://doi.org/10.1177/14614448241303999
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Digital town square? Nextdoor’s offline contexts and online discourse

Published in Journal of Quantitative Description: Digital Media, 2024

There is scant quantitative research describing Nextdoor, the world’s largest and most important hyperlocal social media network… Read more

Recommended citation: Brown, M., Sanderson, Z., Graham, S., Kim, M., Tucker, J., & Messing, S. (2024). Digital town square? Nextdoor’s offline contexts and online discourse. Journal of Quantitative Description: Digital Media , 4. https://doi.org/10.51685/jqd.2024.icwsm.2
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Audio-as-Data Tools: Replicating Computational Data Processing

Published in Media and Communication, 2024

The rise of audio-as-data in social science research accentuates a fundamental challenge: establishing reproducible and reliable methodologies to guide this emerging area of study… Read more

Recommended citation: Lukito, J., Greenfield, J., Yang, Y., Dahlke, R., Brown, M., Lewis, R., & Chen, B. (2024). Audio-as-Data Tools: Replicating Computational Data Processing. Media and Communication, 12, Article 7851. https://doi.org/10.17645/mac.7851
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Estimating the Ideology of Political YouTube Videos

Published in Political Analysis, 2024

We present a method for estimating the ideology of political YouTube videos. The subfield of estimating ideology as a latent variable… Read more

Recommended citation: Lai, A., Brown, M. A., Bisbee, J., Tucker, J. A., Nagler, J., & Bonneau, R. (2024). Estimating the Ideology of Political YouTube Videos. Political Analysis, 1–16. doi:10.1017/pan.2023.42
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Election Fraud, YouTube, and Public Perception of the Legitimacy of President Biden

Published in Journal of Online Trust & Safety, 2022

Skepticism about the outcome of the 2020 presidential election in the United States led to a historic attack on the Capitol on January 6th, 2021 and represents one of the greatest challenges to America’s democratic institutions in over a century. Narratives of fraud… Read more

Recommended citation: Bisbee, J., Brown, M., Lai, A., Bonneau, R., Tucker, J. A., & Nagler, J. (2022). Election Fraud, YouTube, and Public Perception of the Legitimacy of President Biden. Journal of Online Trust and Safety, 1(3). https://doi.org/10.54501/jots.v1i3.60
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SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases

Published in Science of The Total Environment, 2022

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections… Read more

Recommended citation: Wu, F., Xiao, A., Zhang, J., Moniz, K., Endo, N., Armas, F., ... & Alm, E. J. (2022). SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases. Science of The Total Environment, 805, 150121.
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Twitter flagged Donald Trump’s tweets with election misinformation: They continued to spread both on and off the platform

Published in Harvard Misinformation Review, 2021

We analyze the spread of Donald Trump’s tweets that were flagged by Twitter using two intervention strategies—attaching a warning label and blocking engagement with the tweet entirely. We find that… Read more

Recommended citation: Sanderson, Z., Brown, M. A., Bonneau, R., Nagler, J., & Tucker J. A. (2021). 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, 2(4)
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Cross-Platform State Propaganda: Russian Trolls on Twitter and YouTube during the 2016 U.S. Presidential Election

Published in The International Journal of Press/Politics, 2020

This paper investigates online propaganda strategies of the Internet Research Agency (IRA)—Russian “trolls”—during the 2016 U.S. presidential election. We assess claims… Read more

Recommended citation: Golovchenko, Y., Buntain, C., Eady, G., Brown, M. A., & Tucker, J. A. (2020). Cross-Platform State Propaganda: Russian Trolls on Twitter and YouTube during the 2016 U.S. Presidential Election. The International Journal of Press/Politics, 25(3), 357-389. https://doi.org/10.1177/1940161220912682
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Conference Papers

The Digital-Safety Risks of Financial Technologies for Survivors of Intimate Partner Violence

Published in 32nd USENIX Security Symposium, 2023

Digital technologies play a growing role in exacerbating financial abuse for survivors of intimate partner violence (IPV). While abusers of IPV rarely employ advanced technological attacks that go beyond interacting via standard user interfaces… Read more

Recommended citation: Bellini, R., Lee, K., Brown, M. A., Shaffer, J., Bhalerao, R., & Ristenpart, T. (2023). The Digital-Safety Risks of Financial Technologies for Survivors of Intimate Partner Violence. In 32nd USENIX Security Symposium (USENIX Security 23) (pp. 87-104).
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Under Review

Reports & White Papers

The State of Digital Media Data Research, 2024

The purpose of this report is to reflect on the state of digital media data research in 2024. This is the second in a series of reports on the state of digital media research, which we originally published in 2023. We reflect on changes to digital media research since our report in 2023. Specifically, we highlight the following trends: Read more

Recommended citation: Brown, M. A., Lukito, J., Greenfield, J., Chen, B., Graham, S., Shugars, S., & Pruden, M. L. (2024). The State of Digital Media Data Research, 2024. https://doi.org/10.26153/tsw/51921
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The Impact of Twitter API Loss for Research

On Thursday, February 2, 2023, Twitter announced that it planned to end free access to its public API. Recognizing the dramatic impact this would have on public-interest research projects around the globe, the Coalition for Independent Technology Research released an open letter highlighting the disastrous consequences of this decision and began organizing mutual aid for impacted researchers. Those who signed the Coalition’s letter, requested mutual aid, and/or offered to provide such aid could also optionally complete a questionnaire about the impact of the API restrictions on their work. The questionnaire has received 159 responses to date, the results of which are summarized below. Read more

Recommended citation: Brown, M. A., Lukito, J., Yang, K. (2023). The Impact of Twitter API Loss for Research, 2023.
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The State of Digital Media Data Research, 2023

The purpose of this report is to provide an account of digital media data (DMD) research practices and to highlight its ongoing challenges. We define DMD as data that are collected, extracted, gathered, or scraped from a web-based platform such as a website, social networking site, mobile application, or another virtual space. We break these practices and their challenges into three stages—collection, analysis, and sharing. We argue that continuing digital media data (DMD) research should be guided by four principles: collaboration, transparency, preparation, and consistency. Read more

Recommended citation: Lukito, J., Brown, M. A., Dahlke, R., Suk, J., Yang, Y., Zhang, Y., ... & Soorholtz, K. (2023). The state of digital media data research, 2023. http://dx.doi.org/10.26153/tsw/46177
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