Dynamic Processes

Research Focus

Communication is worthy of study because it is capable of producing changes in conversation partners and audiences. I draw on longitudinal survey methods, physiological measures, multilevel structural equation modeling, meta-analysis, and dynamic dyadic systems methods to characterize and dissect the causal processes and dynamics that underlie a broad range of communication experiences.

Key Questions

  • How do communication patterns evolve over time in relationships?
  • What are the causal mechanisms underlying persuasion and influence?
  • How do dyadic interactions create feedback loops that shape outcomes?
  • What temporal dynamics characterize effective social support?

Methodological Approaches

Longitudinal Methods

  • Multi-wave panel surveys
  • Experience sampling methods (ESM)
  • Daily diary studies

Advanced Statistical Modeling

  • Multilevel structural equation modeling (MSEM)
  • Latent growth curve modeling
  • Cross-lagged panel analysis
  • Dynamic systems modeling

Physiological Measures

  • Cardiovascular responses
  • Electrodermal activity
  • Cortisol sampling
  • Neuroimaging techniques

Meta-Analysis

  • Systematic reviews
  • Effect size estimation
  • Moderator analysis

Representative Publications

Zhang, X., & Yan, Y. (2023). Social support seeking on Zhihu among Chinese gay men: Self-disclosure, anonymity, and community responses. Cyberpsychology, Behavior, and Social Networking, 26(7), 518-526. https://doi.org/10.1089/cyber.2022.0364


Contact: zxinyu@msu.edu for collaborations