Conference paper Open Access

Detecting urban structure through inter-city human interactions in China

Willis, George; Gong, Zhaoya; Tranos, Emmanouil

We combine novel inter-city human interaction data with traditional node attribute data to explore
how the Chinese urban network is structured, and how this is associated with the economic
performance of cities in an increasingly urbanising China. We then employ well-established
unsupervised machine learning algorithms to cluster the Chinese cities based on these network
variables and create urban typologies based on mid-term migration patterns. We identify 7 clusters of
cities with shared network characteristics and contrast their economic performances based on more
traditional data. The most disconnected, peripheral cities are also shrinking with a negative population
difference, but are not necessarily the weakest economically, with a reliance on primary industry.

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