Assessing geographic polarisation in Britain’s digital landscape through stable dynamic embedding of spatial web data - Emerald Dilworth; Emmanouil Tranos; Daniel J. Lawson (EPJ Data Science)
Abstract This paper employs Unfolded Adjacency Spectral Embedding (UASE) to investigate the temporal evolution of economic relationships between locations in Great Britain. We utilise timestamped, geolocated website hyperlinks data between archived, commercial websites in Britain, which are aggregated to create a set of directed, weighted networks of hyperlink connections between Local Authority Districts (LADs) for each year in the period 2005-2010. Thus, we are able to assess the digital evolution of longstanding economic disparities such as the North-South, Urban-Rural, and London versus the rest of the country divides in Britain. Our method is a robust and scalable statistical testing procedure for detecting changes between communities in dynamic networks where changes are expressed in terms of known covariates. We can describe network trends over time with respect to longitude and latitude covariates, relying on spatio-temporal stability properties of UASE to make comparisons of nodes in graphs over time. These trends can be formally tested with p-values as well as interpreted in terms of covariates and features of the network. We show how the methodology can be made robust to the problems of large-scale real-world data, used to detect changes over time, and identify their characteristics. This work provides the first robust evidence that commercial website hyperlink connectivity patterns between the North and South are diverging over time, highlighting an increasing digital divide.