Human diffusion and city influence

TL;DR

This paper introduces a method to quantify city influence based on geolocated tweets, revealing how mobility patterns and visitor diversity shape urban hierarchies at different scales.

Contribution

It presents a novel approach to measure city influence using human mobility data and constructs a city network to analyze global and regional centrality.

Findings

Rome and Paris attract diverse visitors consistently.

The ratio of locals to non-locals is key for global influence.

New York and London are top global hubs.

Abstract

Cities are characterized by concentrating population, economic activity and services. However, not all cities are equal and a natural hierarchy at local, regional or global scales spontaneously emerges. In this work, we introduce a method to quantify city influence using geolocated tweets to characterize human mobility. Rome and Paris appear consistently as the cities attracting most diverse visitors. The ratio between locals and non-local visitors turns out to be fundamental for a city to truly be global. Focusing only on urban residents' mobility flows, a city to city network can be constructed. This network allows us to analyze centrality measures at different scales. New York and London play a predominant role at the global scale, while urban rankings suffer substantial changes if the focus is set at a regional level.