From names to numbers: Modelling age and gender profiles from consumer data

Gibin, Maurizio, van Dijk, Justin, Ye, Zi ORCID: 0000-0001-5190-5211 and Longley, Paul (2025) From names to numbers: Modelling age and gender profiles from consumer data Information Geography, 1 (2). 100023-. ISSN 3050-5208

Access the full-text of this item by clicking on the Open Access link.

Abstract

It is axiomatic to Information Geography that, wherever possible, data about human subjects should be created and maintained at the level of the individual. This paper develops and evaluates an innovative approach to inferring the ages of individuals from their given and family names. We use a major UK consumer lifestyles survey alongside baby name statistics to establish the age distributions associated with a comprehensive range of given names. We also use the mix of adult given names within different types of households to refine our age estimates for specific individuals. We evaluate the accuracy of these estimation techniques with respect to (a) specific respondents to a lifestyles survey and (b) UK Census small area estimates. We describe how this approach can be used to ascertain the representativeness of new sources of data and suggest further ways in which the methods might be refined using other contextual information.

Item Type:	Article
Uncontrolled Keywords:	4406 Human Geography, 44 Human Society
Divisions:	Faculty of Science & Engineering Faculty of Science & Engineering > School of Environmental Sciences
Depositing User:	Symplectic Admin
Date Deposited:	01 Oct 2025 07:38
Last Modified:	23 May 2026 10:20
DOI:	10.1016/j.infgeo.2025.100023
Open Access URL:	https://www.sciencedirect.com/science/article/pii/...
Related Websites:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3194675
Disclaimer:	The University of Liverpool is not responsible for content contained on other websites from links within repository metadata. Please contact us if you notice anything that appears incorrect or inappropriate.