Estimating Vertex Measures in Social Networks by Sampling Completions of RDS Trees

Bilal Khan; Kirk Dombrowski; Ric Curtis; Travis Wendel

doi:10.4236/sn.2015.41001

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Social Networking > Vol.4 No.1, January 2015

Estimating Vertex Measures in Social Networks by Sampling Completions of RDS Trees ()

Bilal Khan¹, Kirk Dombrowski², Ric Curtis², Travis Wendel³

¹Department of Math and Computer Science, John Jay College (CUNY), New York, USA.
²Department of Sociology, University of Nebraska-Lincoln, Lincoln, USA.
³St. Ann’s Corner of Harm Reduction, Bronx, USA.

DOI: 10.4236/sn.2015.41001 PDF HTML XML 5,705 Downloads 6,162 Views Citations

Abstract

This paper presents a new method for obtaining network properties from incomplete data sets. Problems associated with missing data represent well-known stumbling blocks in Social Network Analysis. The method of “estimating connectivity from spanning tree completions” (ECSTC) is specifically designed to address situations where only spanning tree(s) of a network are known, such as those obtained through respondent driven sampling (RDS). Using repeated random completions derived from degree information, this method forgoes the usual step of trying to obtain final edge or vertex rosters, and instead aims to estimate network-centric properties of vertices probabilistically from the spanning trees themselves. In this paper, we discuss the problem of missing data and describe the protocols of our completion method, and finally the results of an experiment where ECSTC was used to estimate graph dependent vertex properties from spanning trees sampled from a graph whose characteristics were known ahead of time. The results show that ECSTC methods hold more promise for obtaining network-centric properties of individuals from a limited set of data than researchers may have previously assumed. Such an approach represents a break with past strategies of working with missing data which have mainly sought means to complete the graph, rather than ECSTC’s approach, which is to estimate network properties themselves without deciding on the final edge set.

Keywords

Network Imputation, Missing Data, Spanning Tree Completions, Respondent-Driven Sampling

Share and Cite:

Khan, B. , Dombrowski, K. , Curtis, R. and Wendel, T. (2015) Estimating Vertex Measures in Social Networks by Sampling Completions of RDS Trees. Social Networking, 4, 1-16. doi: 10.4236/sn.2015.41001.

Conflicts of Interest

The authors declare no conflicts of interest.

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