Data-Driven Spatial Models of Human Societies

This 3-year self-funded PhD will be based in the School of Mathematics and Physics and will be supervised by Dr James Burridge.

Despite rapid advances in the connectivity of our modern world it remains true that “everybody’s got to be somewhere”. The mathematical significance of this statement is that the networks of human connections – through which innovations, ideas, language, political opinions and money all travel – are embedded in two dimensional space.

It is well known to statistical physicists that the spatial dimension of a system of interacting particles has a profound impact on their collective behaviour. This observation also applies to human social systems, and recent work[1] has shown that analogies of classical two-dimensional models of interacting atoms may be used to predict the spatial evolution of human language.

At the same time, there has been an explosion in the availability of geographically-located social, economic and textual data generated by governments, charities, social media, local newspapers, businesses and online forums. The aim of this project is first to make use of techniques from statistical learning to search for features from this human output which exhibit significant spatial or spatial-temporal variations, and are therefore powerful predictors of location.

The discovery of these features may then been brought together with our understanding of the ‘‘social physics’’ of human societies to construct models for the evolution of these measurable features, inspired by classical models of statistical physics.

References

[1] J. Burridge Spatial evolution of human dialects. Phys. Rev. X 7, 031008 – Published 17 July 2017

Fees and funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.