Wejnert Cyprian
Cornell University.
Soc Networks. 2010 May 1;32(2):112-124. doi: 10.1016/j.socnet.2009.09.002.
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.
本文介绍了应答驱动抽样法(RDS),这是一种利用调查数据对社会网络进行抽样和分析的可行方法。RDS是一种基于网络的抽样和分析方法,它为以自我为中心的社会网络分析方法和饱和式社会网络分析方法提供了一种折中的补充。该方法与以自我为中心的方法类似,能提供有关通过行为记录的联系而相互关联的个体的调查数据,从而实现对网络结构的宏观层面分析,这与饱和式方法所支持的分析类似。本文以大学生的种族互动为实证例子,通过检验关于跨种族友谊的数量和质量的假设,来研究机构层面的种族多样性在人际层面上是否以及在多大程度上体现为种族融合。然而,本文的主要目的是向网络研究群体介绍RDS,并激发进一步的研究,以实现扩大RDS分析能力的目标。文中还讨论了使用RDS进行网络分析的优点、局限性以及未来研究的方向。