The anatomy of urban social networks and its implications in the searchability problem

TL;DR

This study analyzes large-scale urban social networks from phone data across three countries, revealing that city networks are less geographically clustered and more reliant on community structure for searchability than previously thought.

Contribution

It provides a systematic analysis of urban social network structures at multiple scales, highlighting differences from traditional assumptions and proposing new insights into searchability mechanisms.

Findings

Urban networks are less geographically clustered than expected.

The emergence of a giant component depends on spanning the entire urban area.

Searchability is driven by community structure rather than geographic proximity.

Abstract

The appearance of large geolocated communication datasets has recently increased our understanding of how social networks relate to their physical space. However, many recurrently reported properties, such as the spatial clustering of network communities, have not yet been systematically tested at different scales. In this work we analyze the social network structure of over 25 million phone users from three countries at three different scales: country, provinces and cities. We consistently find that this last urban scenario presents significant differences to common knowledge about social networks. First, the emergence of a giant component in the network seems to be controlled by whether or not the network spans over the entire urban border, almost independently of the population or geographic extension of the city. Second, urban communities are much less geographically clustered than expected. These two findings shed new light on the widely-studied searchability in self-organized networks. By exhaustive simulation of decentralized search strategies we conclude that urban networks are searchable not through geographical proximity as their country-wide counterparts, but through an homophily-driven community structure.