Unpacking Burt’s Constraint Measure

Research output: Contribution to journalArticlepeer-review

Abstract

Burt (1992) proposed two principal measures of structural holes, effective size and constraint. However, the formulas describing the measures are somewhat opaque and have led to a certain amount of confusion. Borgatti (1997) showed that, for binary data, the effective size formula could be written very simply as degree (ego network size) minus average degree of alters within the ego network. The present paper presents an analogous reformulation of the constraint measure. We also derive minima and maxima for constraint, showing that, for small ego networks, constraint can be larger than one, and for larger ego networks, constraint cannot get as large as one. We also show that for networks with more than seven alters, the maximum constraint does not occur in a maximally dense or closed network, but rather in a relatively sparse “shadow ego network”, which is a network that contains an alter (the shadow ego) that is connected to every other alter, and where no other alter-alter ties exist.

Bibliographical metadata

Original languageEnglish
Pages (from-to)50-57
Number of pages8
JournalSocial Networks
Volume62
Early online date27 Feb 2020
DOIs
Publication statusPublished - Jul 2020