SOCIAL NETWORK ANALYSIS WITH RESPONDENT-DRIVEN SAMPLING DATA: A STUDY OF RACIAL INTEGRATION ON CAMPUS

Abstract

This paper presents Respondent-Driven Sampling (RDS) as a viable method of sampling and analyzing social networks with survey data. RDS is a network based sampling and analysis method that provides a middle ground compliment to ego-centric and saturated methods of social network analysis. The method provides survey data, similar to ego-centric approaches, on individuals who are connected by behaviorally documented ties, allowing for macro-level analysis of network structure, similar to that supported by saturated approaches. Using racial interaction of university undergraduates as an empirical example, the paper examines whether and to what extent racial diversity at the institutional level is reflected as racial integration at the interpersonal level by testing hypotheses regarding the quantity and quality of cross-race friendships. The primary goal of this article, however, is to introduce RDS to the network community and to stimulate further research toward the goal of expanding the analytical capacity of RDS. Advantages, limitations, and areas for future research to network analysis using RDS are discussed.

Figure 1

RDS recruitment chains of all 6 productive seeds (enlarged and highlighted with opposite color borders). The nodes are color-coded for gender (male = black, female = gray) and shape-coded for race/ethnicity (White = square, Asian = circle, URM = triangle).