2020/06/19 by Marian-Gabriel Hâncean, Miranda J. Lubbers, José Luis Molina +1 · 17 citations
Computer Science · Mathematics · Social Sciences · #Computer science #Data science #Demography #Diaspora, migration, transnational identity #Geography #Homophily #Migration and Labor Dynamics #Nomination #Political science #Regional science #Residence #Sample (material) #Sampling (signal processing) #Social Capital and Networks #Social media #Social network (sociolinguistics) #Social network analysis #Social science #Sociology #Telecommunications #Tracing #World Wide Web #cs.SI #stat.ME
paper · pdf · doi:10.1371/journal.pone.0253042
published in PLoS ONE 16(6), e0253042 (Public Library of Science) · 37 pages, 8 figures
arxiv created 2020/06/19 · openalex publication_date 2021/06/14 · arxiv updated 2021/07/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We advance bi-national link-tracing sampling design, an innovative data collection methodology for sampling from so-called "transnational social fields", i.e. transnational networks embedding migrants, returned migrants and non-migrants. This paper describes our contributions to this methodology and its empirical implementation, and evaluates the features of the resulting networks (sample), with the aim to guide future research. 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 (Dâmbovița) and in a migration receiving Spanish town (Castellón). 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 link-tracing nomination patterns are affected by sex and residence homophily. Our research contributes to the emerging efforts of applying social network analysis to the study of international migration.