I am Yiwei Xu (Ph.D., 2023, Cornell University), Postdoctoral Scholar at the Center for an Informed Public (CIP) in the Information School at the University of Washington. I am also a Data Science Postdoctoral Fellow at the UW eScience Institute.

My research focuses on examining and developing theory-driven communication strategies that address persistent and emergent public health challenges (e.g., racial disparities, vaccine hesitancy, misinformation, gun violence, etc), with the goal of promoting evidence-based policies and health equity. I also research collective level phenomena in health communication (e.g., collective health information seeking, community level factors that shape media agenda). I conduct experiments, survey, and content analysis by incorporating computational pipelines (e.g., web experiment, supervised machine learning, and digital trace data) to study strategic health communication. I was awarded a Doctoral Dissertation Research Improvement Grant (award #2242458) in Decision, Risk & Management Sciences from the National Science Foundation (NSF) for my dissertation. I also received a Top Paper Award from the International Communication Association (ICA) Information Systems Division.


Methods and Data Analytics

Traditional and Computational Experiments

e.g., Longitudinal panel experiment; Computational experiment with self-programmed mock webpage


e.g., Survey experiment; omnibus survey

Content Analyses

e.g., TV News video content analysis with fine-grained human coding

Machine Learning

e.g., Large-scale content analysis scaled up by supervised machine learning

Big Data Analytics

e.g., Online longitudinal big data analysis (Google Trends) ; Text as data (Large scale news transcription extraction and analysis)

Advanced Statistical Methods

e.g., Multilevel modeling; Time series analysis; Structural equation modeling; etc.

Focused Areas

Social and Psychological Impacts of Generative AI

Xian, L., Li, L., Xu, Y., Zhang, B. Z., & Hemphill, L. (forthcoming). Landscape of generative AI in global news: Topics, sentiments, and spatiotemporal analysis. Proceedings of the International AAAI Conference on Web and Social Media (ICWSM’24)

Dash, S., Xu, Y., & Spiro, E. S. (in progress). Understanding the role of Large Language Models in amplifying heuristic persuasion in disinformation operations.

Liao, W., Xu, Y., Cai, L., & Lin, H. (in progress). Understanding marginalized populations’ emerging beliefs about AI as a source for seeking and processing health and scientific information.

Understanding Online Information Behaviors during Health Crises

Evaluating Media Messaging about Health and Health Equity

Xu, Y., Farkouh, E. K., Dunetz, C. A., Varanasi, S. L., Mathews, S., Gollust, S. E., Fowler, E. F., Moore, S., Lewis, N. A., Niederdeppe, J. (2022). Local TV news coverage of racial disparities in COVID-19 during the first wave of the pandemic, March-June 2020. Race and Social Problems

Neumann, M., Moore, S., Baum, L. M., Oleinikov, P., Xu, Y., Niederdeppe, J., Gollust, S. E., & Fowler, E. F. (2023). Politicizing masks? Examining the volume and content of local news coverage of face coverings in the U.S. through the COVID-19 pandemic. Political Communication

Xu, Y., Neumann, M., Fowler. E. F., Gollust, S. E., & Niederdeppe, J. (in progress). Community characteristics predict local news agenda building about racial health disparities.

Effects of Strategic Messages on Promoting Health Behaviors and Evidenced-Based Policies

Xu, Y., Margolin, D., & Niederdeppe, J. (2021). Testing strategies to increase source credibility through strategic message design in the context of vaccination and vaccine hesitancy. Health Communication, 36(11), 1354-1367. 

Xu, Y., Winett, L. B., Niederdeppe, J. (2021). Evidence of heterogeneity in the direction and magnitude of narrative effects on transportation and counterarguing across three independent samples. International Journal of Communication. 15. 5135–5157.

Niederdeppe, J., Winett, L.B., Xu, Y., Fowler, E. F, & Gollust, S. E. (2021). Evidence-based message strategies to increase public support for state investment in early childhood education: Results from a longitudinal panel experiment. The Milbank Quarterly. 1-44. 

Winett, L. B., Niederdeppe, J., Xu, Y., Gollust, S. E., & Fowler, E. F. (2021). When “tried and true” advocacy strategies backfire: Narrative messages can undermine state legislator support for early childcare policies. The Journal of Public Interest Communications, 5(1), 45-45. 

Ash, E., Xu, Y., Pool, R., Schulenberg, K., Mikkilineni, S. D., & Baraka, T. (2023). Exemplification effects on policy support: Exemplar familiarity, narrative vividness, and perceptions of maternal health disparities. Health Communication.

Xu, Y. (in progress). Communicating controversial risk issues: Effects of inoculation messages on selective exposure and subsequent persuasive outcomes.

Recent Publications

Selected Grants

National Science Foundation (NSF) Doctoral Dissertation Research Improvement Grant in Decision, Risk & Management Sciences. 

“Communicating Controversial Risk Issues - Effects of Inoculation Messages on Selective Exposure to Counterattitudinal Messages and Subsequent Persuasive Outcomes.” $30,168 Total. (Award #2242458)

role: co-PI; PI: Dr. Jeff Niederdeppe

February 2023 – December 2024

University of Washington Center for an Informed Public (CIP) Innovation Fund. 

“Modeling the Role of Large Language Models in Amplifying Strategic (Dis)Information Campaigns and Examining its Persuasive Effects.” $23,465.35 Total. 

role: PI; co-PI: Saloni Dash

March 2024 – September 2024



📧  yiweixu@uw.edu