Geospatial analysis of toponyms in geotagged social media posts

TL;DR

This study analyzes geotagged social media posts to understand how place names are distributed geographically, revealing patterns of spatial inhomogeneity and core-periphery structures that reflect human spatial perception.

Contribution

It introduces a statistical framework for analyzing the spatial distribution of toponyms using social media data, highlighting their non-uniform patterns and decay with distance.

Findings

Toponyms show spatial inhomogeneity distinct from common nouns.

Toponym usage probability decays as a power law with distance from the geographic center.

Identifies core-periphery structures in toponym distributions.

Abstract

Place names, or toponyms, play an integral role in human representation and communication of geographic space. In particular, how people relate each toponym with particular locations in geographic space should be indicative of their spatial perception. Here, we make use of an extensive dataset of georeferenced social media posts, retrieved from Twitter, to perform a statistical analysis of the geographic distribution of toponyms and uncover the relationship between toponyms and geographic space. We show that the occurrence of toponyms is characterized by spatial inhomogeneity, giving rise to patterns that are distinct from the distribution of common nouns. Using simple models, we quantify the spatial specificity of toponym distributions and identify their core-periphery structures. In particular, we find that toponyms are used with a probability that decays as a power law with distance from the geographic center of their occurrence. Our findings highlight the potential of social media data to explore linguistic patterns in geographic space, paving the way for comprehensive analyses of human spatial representations.