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.
Methods and Data Analytics
Traditional and Computational Experiment
e.g., Longitudinal panel experiment; Computational experiment with self-programmed mock webpage
e.g., TV News video content analysis with fine-grained human coding
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.
Understanding Online Collective Behaviors during Health Crises
Evaluating Media Messaging about 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.
Effects of Strategic Messages on Promoting Health Behaviors and Policy Change
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. (revise and resubmit). Exemplification effects on policy support: Exemplar familiarity, narrative vividness, and perceptions of maternal health disparities.
Collective online information seeking during a health crisis: What predicts Google Trends during COVID-19?
Keywords: Online collective behavior, digital trace data, time series analysis, cross sectional analysis
How might selective exposure complicate inoculation effects for controversial social issues?
Keywords: Computational experiment with self-programmed mock web, behavioral measures, selective exposure, inoculation, controversial issues
How are demographic characteristics associated with the volume of local news coverage of racial disparities during COVID-19 pandemic?
Keywords: Community structure model, agenda building, supervised machine learning, multilevel modeling
How do relational motivations influence or bias people's belief in scientific facts on social media?
Keywords: Relational motivations, information processing, social media, science communication