HNDS-R: Population-Scale Kinship Networks and Migration

From the prevalence of genetic diseases to provision of care for elderly, kinship plays an important role in society. Kinship has been shown to be particularly important in providing support to migrants, and migrants, in turn, send money to relatives back home, but the typical methods used to study contemporary migration cannot show its long-term effects upon kin networks in space. Data at a larger temporal and spatial scale are needed. This project creates a population-scale family tree dataset which links about forty million people in crowd-sourced family trees to their common ancestors. The research will use these data to study how migration influenced the geographic proximity of kin over centuries. This project contributes to the development of globally competitive STEM workforce by training graduate, undergraduate and high school students in the areas of human networks and data science. It develops an online visual storytelling and education tool to communicate how migrations form cultural and demographic structures. This tool, which is being developed through a collaboration with high school social studies teachers, has the potential to increase public scientific literacy about and engagement in the study of migration and kinship networks.This research compares the spatial evolution of kinship networks under different conditions to test theories about how and when different types of networks emerge, stagnate, and, ultimately, disappear, showing how those networks change as a result of a variety of economic and demographic circumstances. The project links information such as occupation, household composition, and fine-scale locations of residences from the historical census data to the family trees. This data can then be used to characterize kinship networks and their evolution over geographic space and time. This research helps reveal the conditions that favor the development of large aggregations of related families, and those that favor dispersion. Specifically, this project assesses how much migration contributed to the development of different types of networks and how this relationship changed as different locations were settled by different groups. This research helps bridge the gap between geographic information science and social network analysis by developing new measures, models, and visualization techniques for studying the relationship between kinship networks and migration. The data will allow researchers to study how the proximity of family members influences a variety of other long-term multi-generational outcomes such as income inequality, social mobility, and health. A better understanding of the forces that transform kinship networks and methods for describing them helps anticipate changes in the present and future, such as the extent to which elderly or vulnerable populations can rely on kin nearby for support.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.