A Practical Guide to Measuring Social Structure Using Indirectly Observed Network Data

Abstract

Aggregated relational data (ARD) are an increasingly common tool for learning about social networks through standard surveys. Recent statistical advances present social scientists with new options for analyzing such data. In this article, we propose guidelines for learning about various network processes using ARD and a template to aid practitioners. We first propose that ARD can be used to measure “social distance” between a respondent and a subpopulation (individuals named Kevin, those in prison, or those serving in the military). We then present common methods for analyzing these data and associate each of these methods with a specific way of measuring social distance, thus associating statistical tools with their underlying social science phenomena. We examine the implications of using each of these social distance measures using an Internet survey about contemporary political issues.

Keywords:

• 62-07
• 62P25
• 91D30

Keywords:

• Aggregated relational data
• hierarchical model
• opinion formation
• sampling bias
• overdispersed Poisson distribution
• sample survey
• social network

Acknowledgments

We thank the National Science Foundation, Columbia Population Research Center, and Columbia Applied Statistics Center for supporting this research. This work was partially completed while Tyler McCormick was supported by a Google PhD Fellowship in Statistics. We also appreciate comments by two referees and the editor.

Notes

The first three authors contributed equally to this paper.