Measuring transnational social fields through binational link-tracing sampling

TL;DR

This study develops and tests a binational link-tracing sampling method to analyze transnational social networks involving migrants and non-migrants, revealing network structures and methodological challenges in migration research.

Contribution

It introduces an innovative binational sampling design for transnational networks and offers practical insights and methodological improvements for social network analysis in migration studies.

Findings

Constructed a multi-layered network with 4,855 nodes and 5,477 ties.

Identified challenges in participant identification and sample representativeness.

Demonstrated the method's utility in exploring social organization and connectivity of migrant communities.

Abstract

We advance binational link-tracing sampling design, an innovative data collection methodology for sampling from transnational social fields, i.e., transnational networks embedding migrants and non-migrants. This paper shows the practical challenges of such a design, the representativeness of the samples and the qualities of the resulted networks. We performed 303 face-to-face structured interviews on sociodemographic variables, migration trajectories and personal networks of people living in a Romanian migration sending community (D\^ambovi\c{t}a) and in a migration receiving Spanish town (Castell\'on), simultaneously in both sites. Inter-connecting the personal networks, we built a multi-layered complex network structure embedding 4,855 nominated people, 5,477 directed ties (nominations) and 2,540 edges. Results indicate that the participants' unique identification is a particularly difficult challenge, the representativeness of the data is not optimal (homophily on observed attributes was detected in the nomination patterns), and the relational and attribute data allow to explore the social organization of the Romanian migrant enclave in Castell\'on, as well as its connectivity to other places. Furthermore, we provide methodological suggestions for improving link-tracing sampling from transnational networks of migration. Our research contributes to the emerging efforts of applying social network analysis to the study of international migration.