Research

Political violence, online extremism, and computational social science

How do online communities translate into offline political action?

I treat digital platforms not as communication channels but as constitutive environments, where political identities form, grievances are framed, and collective action is coordinated. Answering that question at scale requires measurement strategies that traditional survey and interview methods cannot supply, so my empirical work combines transformer-based text models, network analysis, and time-series causal inference with archival and qualitative work on the communities themselves.

A longer version of this agenda is on the research statement page. Code, models, and datasets are described under code and data.

Job market paper

“The Happening Is Coming”: Apocalyptic Rhetoric on 4chan Following Mass-Casualty Attacks

I train a transformer classifier to measure apocalyptic rhetoric across eleven years of 4chan /pol/ posts, then use intervention analysis to test how that measure responds to mass-casualty terrorist attacks. Apocalypticism rises sharply in the immediate aftermath of attacks, providing evidence of a feedback loop between digital communities and offline violence. Presented at APSA 2025; draft available on request.

Dissertation overview · Request the paper

Publications

Peer-reviewed articles

Newhouse, A. and Kowert, R. (2025). “Extremist Identity Creation Through Performative Infighting on Steam.” Frontiers in Psychology.

Extremist identity crystallizes through performative displays of ideological purity and intra-group conflict, showing how gaming communities sustain cohesion and radicalization without central leadership.

Gaming Extremism Identity formation

Kowert, R., Kilmer, E., and Newhouse, A. (2024). “Taking it to the Extreme: Prevalence and Nature of Extremist Sentiment in Games.” Frontiers in Psychology, 15:1410620.

A survey of 423 game players measuring the prevalence, location, and impact of extremist sentiment in games. More than half of players report encountering hate, harassment, or abuse in gaming spaces. Funded by the Department of Homeland Security (EMW-2022-GR-00036).

Gaming Survey research Online harm

Kowert, R., Kilmer, E., and Newhouse, A. (2024). “Culturally Justified Hate: Prevalence and Mental Health Impact of Dark Participation in Games.” Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS).

Gaming Online harm Mental health

Newhouse, A. (2021). “The Threat is the Network: The Multi-Node Structure of Neo-Fascist Accelerationism.” CTC Sentinel, 14(5).

Atomwaffen Division was not the apex of a hierarchy but one node in a larger network of violent accelerationists held together by membership fluidity, frequent communication, and a shared goal of social collapse — with the implication that enforcement against individual groups is necessary but not sufficient.

Networks Accelerationism Political violence

Under review

Benton, A., Newhouse, A., and Philips, A. “Mind the Gap! Policy Dissonance and Financial Markets.” Under review.

Newhouse, A., Kaur, K., and Philips, A. “Partisan Polarization Shapes Visual Framing of COVID-19 in U.S. Media.” Under review.

Book chapters

Newhouse, A. and Kowert, R. (2025). “Recruitment and mobilization in digital gaming spaces.” In L. Schlegel (ed.), Handbuch Gaming & Rechtsextremismus.

Kowert, R. and Newhouse, A. (2025). “Digital games as cultural assets of influence.” In S. Lakhani and A. Amarasingam (eds.), The Sociology of Violent Extremism.

Newhouse, A. and Kowert, R. (2024). “Digital games as vehicles for extremist recruitment and mobilization.” In L. Schlegel and R. Kowert (eds.), Gaming and Extremism: The Radicalization of Digital Playgrounds.

Preprints and research reports

McGuffie, K. and Newhouse, A. (2020). “The Radicalization Risks of GPT-3 and Advanced Neural Language Models.” arXiv preprint 2009.06807.

Among the first assessments of generative language model misuse risk, showing that GPT-3 could produce interactive and influential content usable for far-right radicalization.

AI safety LLM misuse Extremism

Kriner, M., Conroy, M., Newhouse, A., and Lewis, J. (2022). “Understanding Accelerationist Narratives: The Great Replacement Theory.” Global Network on Extremism and Technology.

Shadnia, D., Newhouse, A., Kriner, M., and Bradley, A. (2022). “Militant Accelerationism Coalitions: A Case Study in Neo-Fascist Accelerationist Coalition-Building Online.” CTEC.

Kowert, R., Botelho, A., and Newhouse, A. (2022). “Breaking the Building Blocks of Hate: A Case Study of Minecraft Servers.” Anti-Defamation League.

A full list, including public writing and earlier reports, is in the CV and on the writing page.

Current projects

Dissertation — Social Processes and Collective Mobilization in the Online Extreme Right

How decentralized, leaderless online extremist communities produce collective mobilization in the absence of formal hierarchy. Three empirical chapters use transformer NLP, interrupted time-series and intervention analysis, network contagion models, and novel datasets drawn from 4chan, Iron March, and mass-casualty attack archives. Prospectus defended April 2026; expected defense May 2028. Full overview.

Committee: Andrew Q. Philips and Jennifer Fitzgerald (co-chairs), Alexandra Siegel, with Brian Keegan (Information Science) as external advisor.

Partisan framing of the pandemic

With Andrew Q. Philips and Komal P. Kaur. Partisan differences in the visual and textual framing of COVID-19 coverage across U.S. news outlets, using computer vision alongside text analysis. Presented at APSA 2025 and MPSA 2025; under review.

Policy dissonance and financial markets

With Allyson L. Benton and Andrew Q. Philips. How gaps between political rhetoric and policy action move financial markets. Under review.

The American humanities workforce

A large-scale computational study of humanities career trajectories using anonymized LinkedIn data, conducted at the National Humanities Alliance. The measurement strategy combines ensembles of local LLMs with conventional NLP for free-text career histories.

Gaming platforms and political socialization

Continuing work with Rachel Kowert on recruitment and radicalization in digital gaming environments, including applied collaborations with platforms on harm mitigation.

Methods

Text as data. Transformer fine-tuning for political concepts (PyTorch, Hugging Face), classical supervised text classification, and validation strategies for contested constructs. See the worked example of a DistilBERT classifier for political text.

Networks. Diffusion and contagion across forum and cross-platform networks, using igraph and statnet.

Causal inference with time series. Interrupted time-series and intervention analysis for online–offline effects, plus regression with novel observational datasets.

Data collection. Large-scale archival social media collection, survey design, and qualitative coding under sensitive-data constraints.

Data, code, and collaboration

Replication materials, classifiers, and dataset documentation are described on the code and data page. For collaboration, data access, or media requests, email alex.newhouse@colorado.edu.

Google Scholar · ORCID 0009-0003-6346-9527 · GitHub

Last updated: August 2026

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