Nathan TeBlunthuis

Nathan TeBlunthuis

Assistant Professor


Biography

Dr. Nathan TeBlunthuis is a computational social scientist who studies organizing in digital environments including Wikipedia, Reddit, and platforms for collective action. His research analyzes machine learning technologies as used in such communities and by social scientists. He also focuses on understanding how relationships among organizations shape each other's success in these contexts, drawing from organizational ecology, and on advancing methods for doing so. He primarily works with large datasets of behavioral digital traces and uses computational methods such as natural language processing, machine learning, and causal inference from observational data. He earned his Ph.D. from the University of Washington Department of Communication in 2021 and is currently a Postdoctoral Research Fellow at the University of Michigan School of Information. His first-authored works have been published in top venues in both computing and communication and have won top paper awards from the Computational Methods Division of the International Communication Association in the past three consecutive years.

Degrees

PhD University of Washington Department of Communication

Areas Of Specialization

Peer Production
Computational Social Science
Online Communities
Statistics
Big Data
Machine Learning
collective action
Wikipedia

Recent Publications

TeBlunthuis, Nathan, Benjamin Mako Hill, and Aaron Halfaker. 2021. Effects of al-gorithmic flagging on fairness: Quasi-experimental evidence from Wikipedia.In Proceedings of the ACM: Human-Computer Interaction (CSCW). 56:1-56:27.https://doi.org/10.1145/3449130.

TeBlunthuis, Nathan. 2021. Measuring Wikipedia Article Quality in One Dimen-sion. In Proceedings of the 17th International Symposium on Open Collabora-tion (OpenSym 21). Online: ACM Press. https://doi.org/10.1145/3479986.3479991.

TeBlunthuis, Nathan, Charles Kiene, Isabella Brown, Nicole McGinnis, Laura (Alia)Levi, and Benjamin Mako Hill. 2022. No Community Can Do Everything:Why People Participate in Similar Online Communities. In Proceedings ofthe ACM: Human-Computer Interaction (CSCW). https://dl.acm.org/doi/10.1145/3512908.

TeBlunthuis, Nathan, and Benjamin Mako Hill. 2022. Identifying Competitive andMutualistic Relationships Between Online Communities. In InternationalAAAI Conference on Web and Social Media (ICWSM 2022) https://ojs.aaai.org/index.php/ICWSM/article/view/19352/19124.

TeBlunthius, Nathan, Valarie Hase, and Chung-hong Chan. 2023. Misclassificationin Automated Content Analysis Causes Bias in Regression. Can We Fix It?Yes We Can! In Communication Methods and Measures. https://arxiv.org/abs/2307.06483. Accepted.

Colglazier, Carl, Nathan TeBlunthuis, and Aaron Shaw The Effects of Group Sanc-tions on Participation and Toxicity: Quasi-experimental Evidence from theFediverse. In International AAAI Conference on Web and Social Media (ICWSM2024)

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Recent Courses

YearSemesterCourse NumberCourseSyllabusNotes
2025SpringI 306Statistics for Informatics
2024FallI 320UTopics in User Experience Design: Online Communities
2024FallI 320STopics in Social Informatics: Online Communities