I'm Anna Beers. I received my PhD from the University of Washington's Human-Centered Design and Engineering program (HCDE). I study political social media influencers, science communication, mis/disinformation, and other "bad things on the internet" using network science, machine learning, and mixed methods.

You can see a list of selected publications below, as well as some portfolio items. You can see a full publication list on my Google Scholar profile. my CV at this link, and some of my coding projects on my Github account.

Last updated September 18, 2023.

Anna Beers, Sarah Nguyễn, Kate Starbird, Jevin D. West, and Emma S. Spiro. 2023. Selective and deceptive citation in the construction of dueling consensuses. Science Advances.

Anna Beers, Joseph S. Schafer, Ian Kennedy, Morgan Wack, Emma S. Spiro, and Kate Starbird. 2023. Followback Clusters, Satellite Audiences, and Bridge Nodes: Coengagement Networks for the 2020 US Election. In Proceedings of the International AAAI Conference on Web and Social Media, 59–71.

Anna Beers, Tom Wilson, and Kate Starbird. 2022. The Demographics of an International Influence Operation Affecting Facebook Users in the United States. Journal of Online Trust and Safety 1

Joseph B. Bak-Coleman, Ian Kennedy, Morgan Wack, Anna Beers, Joseph S. Schafer, Emma S. Spiro, Kate Starbird, and Jevin D. West. 2022. Combining interventions to reduce the spread of viral misinformation. Nature Human Behaviour 6, 10: 1372–1380.

Ian Kennedy, Morgan Wack, Anna Beers, Joseph S. Schafer, Isabella Garcia-Camargo, Emma S. Spiro, and Kate Starbird. 2022. Repeat Spreaders and Election Delegitimization: A Comprehensive Dataset of Misinformation Tweets from the 2020 U.S. Election. Journal of Quantitative Description: Digital Media 2.

Anna Beers. 2023. Negative Influencers in Social Networks: From Targeted Harassment to Controversy Cultivation. International Network for Social Network Analysis (Sunbelt).

Anna Beers. 2023. Two Years of Influence: Tracking Changes in Twitter Influencer Diets in United States Politics. International Conference on Computational Social Science (IC2S2)

Anna Beers, Kennedy, Ian, Morgan Wack, Joseph S. Schafer, Emma S. Spiro, and Kate Starbird. 2022. Repeat Offenders: Frequent and Influential Misinformation Sources During the 2020 United States Election. International Studies Association

Anna Beers. 2021. Misinterpretation and Ambiguity in Public-Facing Network Visualizations: A Case Study.

Anna Beers, Sarah Nguyễn, Maya Sioson, Mariam Mayanja, Monica Ionescu, Emma S. Spiro, and Kate Starbird. 2021. The Firestarting Troll, and Designing for Abusability. International AAAI Conference on Web and Social Media, Information Credibility & Alternative Realities in Troubled Democracies Workshop

Anna Beers, Sarah Nguyễn, Emma S. Spiro, and Kate Starbird. 2021. Rejecting Science with Science: Boundary-Work in Anti-Mask Twitter Reply Threads During COVID-19. AoIR Selected Papers of Internet Research.

Anna Beers, Melinda McClure Haughey, Ahmer Arif, and Kate Starbird. 2020. Examining the digital toolsets of journalists reporting on disinformation. Computation + Journalism

Anna Beers, James Brown, Ken Chang, Katharina Hoebel, Jay Patel, K. Ina Ly, Sara M. Tolaney, Priscilla Brastianos, Bruce Rosen, Elizabeth R. Gerstner, and Jayashree Kalpathy-Cramer. 2020. DeepNeuro: an open-source deep learning toolbox for neuroimaging. Neuroinformatics.

Ken Chang, Anna L. Beers, Laura Brink, Jay B. Patel, Praveer Singh, Nishanth T. Arun, Katharina V. Hoebel, Nathan Gaw, Meesam Shah, Etta D. Pisano, Mike Tilkin, Laura P. Coombs, Keith J. Dreyer, Bibb Allen, Sheela Agarwal, and Jayashree Kalpathy-Cramer. 2020. Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density. Journal of the American College of Radiology 17, 12: 1653–1662.

Ken Chang, Anna L. Beers (first co-author), Harrison X. Bai, James M. Brown, K. Ina Ly, Xuejun Li, Joeky T. Senders, Vasileios K. Kavouridis, Alessandro Boaro, Chang Su, Wenya Linda Bi, Otto Rapalino, Weihua Liao, Qin Shen, Hao Zhou, Bo Xiao, Yinyan Wang, Paul J. Zhang, Marco C. Pinho, Patrick Y. Wen, Tracy T. Batchelor, Jerrold L. Boxerman, Omar Arnaout, Bruce R. Rosen, Elizabeth R. Gerstner, Li Yang, Raymond Y. Huang, and Jayashree Kalpathy-Cramer. 2019. Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement. Neuro-Oncology 21, 11: 1412–1422.

Anna Beers, Ken Chang, James Brown, Elizabeth Gerstner, Bruce Rosen, and Jayashree Kalpathy-Cramer. 2018. Sequential neural networks for biologically informed glioma segmentation. In Medical Imaging 2018: Image Processing, 1057433.

Anna Beers, James Brown, Ken Chang, J. Peter Campbell, Susan Ostmo, Michael F. Chiang, and Jayashree Kalpathy-Cramer. 2018. High-resolution medical image synthesis using progressively grown generative adversarial networks. arXiv:1805.03144 [cs].