Abstract
ABSTRACT We introduce a method to calculate and store approximately 1.2 million surname distributions calculated for surnames found in Great Britain for six years of historic population data and 20 years of contemporary population registers compiled from various consumer sources. We subsequently show how this database can be incorporated into an interactive web-environment specifically designed for the public dissemination of detailed surname statistics. Additionally, we argue that the database can be used in the quantitative analysis of surnames in Great Britain and potentially offer valuable insights into processes of contagious and hierarchical diffusion of populations as well as the regional distinctiveness of demographic change and stasis.
Highlights
When it comes to hereditary surnames or family names, two important observations can be made
We subsequently show how this database can be incorporated into a contemporary web-environment, how we can interactively map the calculated surname distributions, and how consumer statistics can be linked to the calculated surname distributions to create individual surname profiles
We subsequently describe the spatial patterns of the population-weighted point events on a year-by-year and surname-by-surname basis through a process called Kernel Density Estimation (KDE)
Summary
When it comes to hereditary surnames or family names, two important observations can be made. As a result of varying socio-spatial differences in naming practices, surnames can be traced back to a national or regional origin (Cheshire, 2014; Cheshire et al, 2010; Cheshire & Longley, 2012). Because of these properties, together with their relatively high level of availability, surnames have been used in a variety of studies, ranging from inferring ethnicity (Lan et al, 2018; Mateos et al, 2011) to identifying probable genetically close individuals for sampling purposes (Kandt et al, 2016). We argue that the database can be used for further research, and can potentially offer valuable insights into processes of contagious and hierarchical diffusion of populations as well as the regional distinctiveness of demographic change and stasis (see Van Dijk et al, 2019; Van Dijk & Longley, 2020)
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