Egocentric Network Analysis:
An Avenue for Social Work Research
Two-Day Intensive Workshop
Date: Monday, April 13 & Tuesday, April 14, 2026
Time: 8:00 am - 4:00 pm (Break from 12:00 - 1:00)
Location: Okazaki Community Meeting Room (SW 155-A), College of Social Work
Overview
This workshop provides a practical, research‑focused introduction to egocentric (personal) network analysis for faculty and advanced scholars interested in incorporating network approaches into their work. The workshop moves beyond conceptual overviews to focus on how to design, measure, manage, and analyze ego network data, with attention to common methodological challenges and best practices.
Participants will engage with the full research enterprise, from framing network‑based research questions and selecting appropriate data collection strategies, to computing and interpreting structural and compositional network measures. Examples are drawn from health, social behavior, family, and life‑course research, with emphasis on how ego network methods extend traditional quantitative and mixed‑methods approaches.
Objectives
By the end of the workshop, participants will be able to:
- Translate substantive research questions into ego network designs, identifying when egocentric methods are preferable to proxy measures or sociocentric approaches.
- Design ego network instruments, including informed selection of name generators, name interpreters, and boundary‑definition strategies.
- Collect and structure ego network data for analysis, understand alternative data formats (wide vs. long), and assess their implications for modeling.
- Compute and interpret core ego network measures, including network size, density, heterogeneity, homophily, multiplexity, structural holes, and constraint.
- Evaluate data quality and sources of bias in ego network research, including recall, respondent burden, and measurement error.
- Apply appropriate analytic strategies to ego network data, including ego-level aggregation, multilevel modeling, and longitudinal approaches.
- Integrate ego network measures into regression and multilevel models and interpret
network effects alongside individual‑level predictors.
About Presenter
David Kondrat, PhD, is a Professor and Chair of Social Work and Sociology at North Carolina A&T State University. He is an expert in ego network analysis, with a research focus on how personal networks, particularly family and close ties, shape social support, stress, stigma, and well-being. His work integrates network structure, relational dynamics, and lived experience to advance understanding of mental health and social systems, with particular attention to serious mental illness.
Registration
Seating is limited to 30 participants