Modelling Name Dynamics

Bethany Delves

doi:10.59973/emjsr.420

Authors

Bethany Delves University of Portsmouth, School of Mathematics and Physics, Portsmouth, PO1 3QL, UK

DOI:

https://doi.org/10.59973/emjsr.420

Keywords:

Onomastics, Wright-Fisher Model, Population Genetics, Stochastic Modelling, Time-dependent Bias

Abstract

This paper investigates the mathematical modelling of name dynamics, using a stochastic model applied to data from the Office for National Statistics (ONS). Building on the Wright-Fisher model from population genetics, bias is incorporated to represent preferential selection, while mutation is introduced to account for random individual variation in naming behaviour. The parameters are fitted to the ONS name data and multiple formulations of the bias function are evaluated to determine the best representation of observed trends. The results demonstrate that incorporating mutation and a time-dependent bias substantially improves the fit to data and produces realistic forecasts of future trends. The proposed model captures key features of changing name popularity while remaining computationally efficient, illustrating the potential of stochastic population models to capture the dynamics of cultural evolution in naming practices.

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