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15 - From Edward O. Laumann, Peter V. Marsden, and David Prensky, “The Boundary Specification Problem in Network Analysis”

from III - Later Foundations

Published online by Cambridge University Press:  01 October 2021

Edited by
Mario L. Small ,
Brea L. Perry ,
Bernice Pescosolido  and
Edward B. Smith
Mario L. Small
Affiliation:
Harvard University, Massachusetts
Brea L. Perry
Affiliation:
Indiana University, Bloomington
Bernice Pescosolido
Affiliation:
Indiana University, Bloomington
Edward B. Smith
Affiliation:
Northwestern University, Illinois
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Summary

In their influential chapter on the boundary specification problem in network analysis, Laumann, Marsden, and Prensky (1989) argued that social network data often do not mirror the true underlying social structures in which individuals are embedded. Rather, the validity of network data hinges on the alignment of network boundaries and the social system or social mechanisms being studied. For this reason, the process of determining which actors and relationships should be included in a network is among the most critical research design issues in social network analysis, requiring a tight alliance of theory and method. Here, we build on Laumann and coauthors’ insights, updating their review with contemporary examples, and extending their ideas to the personal network research design context. We begin by identifying characteristics of personal network research, such as boundary spanning, that introduce unique challenges and opportunities to the boundary definition issue. We then apply concepts from their typology, reviewing common strategies for establishing boundaries through name generators in the context of personal network research designs.

Keywords

Personal social networksEgocentric networksBoundary specificationName generatorsName interpretersRealist versus nominalist approachesFunctional specificity
Type
Chapter
Information
Personal Networks
Classic Readings and New Directions in Egocentric Analysis
 , pp. 417 - 430
Publisher: Cambridge University Press
Print publication year: 2021

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