- Copyright page
- Acknowledgments
- Editor Biographies
- Contributor Biographies
- Introduction
- Network Basics: Points, Lines, and Positions
- Theories of Social Networks
- Networks and Neo-Structural Sociology
- Rethinking Social Networks in the Era of Computational Social Science
- Networks, Status, and Inequality
- Strategies for Collecting Social Network Data: Overview, Assessment, and Ethics
- Social Network Experiments
- The Network Scale-Up Method
- The Continued Relevance of Ego Network Data
- Dyadic, Nodal, and Group-Level Approaches to Study the Antecedents and Consequences of Networks: Which Social Network Models to Use and When?
- An Introduction to Statistical Models for Networks
- Advances in Exponential Random Graph Models
- Modeling Network Dynamics
- Causal Inference for Social Network Analysis
- Case Studies in Network Community Detection
- Three Perspectives on Centrality
- Network Visualization
- The Spatial Dimensions of Social Networks
- Field Experiments of Preferential Attachment
- Duality beyondPersons and Groups: Culture and Affiliation
- Networks of Culture,Networks of Meaning: Two Approaches to Text Networks
- Historical Network Research
- Networks in Archaeology
- Networks, Kin, and Social Support
- Demography and Networks
- The Neuroscience of Social Networks
- Computational Social Science, Big Data, and Networks
- Networks: An Economic Perspective
- Social Capital and Economic Sociology
- The International Trade Network
- Maps of Science, Technology, and Education
- Criminal Networks
- Index
Abstract and Keywords
This chapter provides an overview of social network data collection strategies. We begin by outlining the primary principles of sampling and measurement design, then describing how those combine into what is labeled the “boundary specification problem” for social network research. We accompany these definitions with examples of how these elements are applied across ego, partial, and complete network designs. Next, the chapter turns to the primary ways that network data have been evaluated, highlighting both the implications of those evaluations for their use in network analyses and various strategies for how the identified limitations can be leveraged for optimal data and analytic quality. The chapter concludes by addressing some of the ethical considerations that are unique to the gathering and analyses of social network data.
Keywords: data collection, survey design, data quality, research ethics, name generators, name interpreters, relational interpreters
jimi adams is Associate Professor in the Department of Health and Behavioral Sciences at the University of Colorado Denver. His work focuses on examining social networks to understand how infectious diseases and novel ideas spread. This has included modeling HIV/AIDS risk in the United States and Sub-Saharan Africa, and the organizational dynamics of interdisciplinary fields. He is the author of Gathering Social Network Data.
Tatiane Santos is a postdoctoral fellow at the Wharton School at the University of Pennsylvania and adjunct faculty at the Colorado School of Public Health. Her research has focused on evaluating the impact of the Patient Protection and Affordable Care Act provisions on population health outcomes, health care utilization, and costs. She is primarily interested in public health services and systems research specific to policies and reimbursement reforms that encourage institutions in the health care and governmental public health sectors to align efforts to improve population health. She has evaluated Colorado’s Medicaid reform efforts, as well as Colorado’s state innovation model that seeks to integrate primary care and behavioral health. She is interested in applying organization theory and social network methods to explore the role of community social capital in promoting public health.
Venice Ng Williams is a Post-doctoral Mixed Methods Researcher at the University of Colorado Prevention Research Center for Family and Child Health. She received her PhD in Health Services Research from the Colorado School of Public Health and is trained in program planning, evaluation, and econometrics. Her research focuses on mixed methods, maternal-child health, organizational collaboration, and translating research into practice within the context of prevention programs. She has previously worked in health promotion, tobacco prevention policies, systems change evaluation, health impact assessments, and hospital community-benefit research.
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- Copyright page
- Acknowledgments
- Editor Biographies
- Contributor Biographies
- Introduction
- Network Basics: Points, Lines, and Positions
- Theories of Social Networks
- Networks and Neo-Structural Sociology
- Rethinking Social Networks in the Era of Computational Social Science
- Networks, Status, and Inequality
- Strategies for Collecting Social Network Data: Overview, Assessment, and Ethics
- Social Network Experiments
- The Network Scale-Up Method
- The Continued Relevance of Ego Network Data
- Dyadic, Nodal, and Group-Level Approaches to Study the Antecedents and Consequences of Networks: Which Social Network Models to Use and When?
- An Introduction to Statistical Models for Networks
- Advances in Exponential Random Graph Models
- Modeling Network Dynamics
- Causal Inference for Social Network Analysis
- Case Studies in Network Community Detection
- Three Perspectives on Centrality
- Network Visualization
- The Spatial Dimensions of Social Networks
- Field Experiments of Preferential Attachment
- Duality beyondPersons and Groups: Culture and Affiliation
- Networks of Culture,Networks of Meaning: Two Approaches to Text Networks
- Historical Network Research
- Networks in Archaeology
- Networks, Kin, and Social Support
- Demography and Networks
- The Neuroscience of Social Networks
- Computational Social Science, Big Data, and Networks
- Networks: An Economic Perspective
- Social Capital and Economic Sociology
- The International Trade Network
- Maps of Science, Technology, and Education
- Criminal Networks
- Index
