Do Human Mobility Network Analyses Produced from Different Location-based Data Sources Yield Similar Results across Scales?

TL;DR

This study compares human mobility network analyses from three major location-based data sources across different scales, revealing significant differences and emphasizing the need for ground-truth datasets to ensure result reliability.

Contribution

It provides an empirical comparison of human mobility measures from Spectus, X-Mode, and Veraset datasets across multiple scales, highlighting dataset sensitivity.

Findings

Different datasets produce dissimilar mobility network results

Results are sensitive to the choice of data source

Ground-truth datasets are necessary for validation

Abstract

The burgeoning availability of sensing technology and location-based data is driving the expansion of analysis of human mobility networks in science and engineering research, as well as in epidemic forecasting and mitigation, urban planning, traffic engineering, emergency response, and business development. However, studies employ datasets provided by different location-based data providers, and the extent to which the human mobility measures and results obtained from different datasets are comparable is not known. To address this gap, in this study, we examined three prominent location-based data sources: Spectus, X-Mode, and Veraset to analyze human mobility networks across metropolitan areas at different scales: global, sub-structure, and microscopic. Dissimilar results were obtained from the three datasets, suggesting the sensitivity of network models and measures to datasets. This finding has important implications for building generalized theories of human mobility and urban dynamics based on different datasets. The findings also highlighted the need for ground-truthed human movement datasets to serve as the benchmark for testing the representativeness of human mobility datasets. Researchers and decision-makers across different fields of science and technology should recognize the sensitivity of human mobility results to dataset choice and develop procedures for ground-truthing the selected datasets in terms of representativeness of data points and transferability of results.