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Summary
This summary is machine-generated.

This study quantifies city influence using geolocated tweets to analyze human mobility. Global city influence depends on attracting diverse visitors, with New York and London central on a global scale.

Keywords:
city–city interactionepidemiologygeolocated datahuman mobilitynetworks

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Area of Science:

  • Urban Studies
  • Network Science
  • Computational Social Science

Background:

  • Cities concentrate population, economic activity, and services, leading to natural hierarchies at various scales.
  • Understanding city influence and hierarchy is crucial for urban planning and global economic analysis.

Purpose of the Study:

  • To introduce a novel method for quantifying city influence by analyzing human mobility patterns.
  • To investigate the factors contributing to a city's global reach and hierarchical position.
  • To construct and analyze city-to-city networks based on urban residents' mobility flows.

Main Methods:

  • Utilizing geolocated tweets to characterize and quantify human mobility patterns.
  • Developing a network-based approach to analyze city centrality at different scales.
  • Calculating the ratio of local to non-local visitors to assess a city's global status.

Main Results:

  • Rome and Paris were identified as cities attracting the most diverse visitors.
  • The ratio of local to non-local visitors is a key indicator of a city's global significance.
  • New York and London emerged as central nodes in the global city network.
  • Urban rankings significantly shifted when analyzed at a regional versus global scale.

Conclusions:

  • Human mobility data from geolocated tweets provides a robust method for assessing city influence.
  • A city's global standing is influenced by its ability to attract a diverse range of visitors.
  • Network analysis reveals distinct urban hierarchies at global and regional levels, highlighting the importance of scale.