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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

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Measuring Global Multi-Scale Place Connectivity using Geotagged Social Media Data.

Zhenlong Li¹, Xiao Huang², Xinyue Ye³

¹Geoinformation and Big Data Research Laboratory, Department of Geography, University of South Carolina, SC, USA.

|February 10, 2021

Summary

This study introduces a novel global multi-scale place connectivity index (PCI) using geotagged social media data. PCI effectively quantifies human movement patterns and demonstrates potential in real-world applications like disease modeling.

Keywords:

Facebook SCI SafeGraph Twitter big data place connectivity spatial interaction

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Area of Science:

Spatial analysis and human geography
Geospatial big data analytics
Social network analysis

Background:

Place connectivity is crucial for understanding human movement and spatial interactions.
Traditional methods for measuring connectivity are limited.
Social media data offers a novel, accessible, and privacy-conscious source for spatial interaction analysis.

Approach:

Developed a global multi-scale place connectivity index (PCI) using geotagged social media data.
Validated PCI against SafeGraph population movement records and Facebook's Social Connectedness Index (SCI).
Analyzed PCI's spatial characteristics, including boundary effects and distance decay.

Key Points:

PCI demonstrates a strong positive association with established movement and social connectivity metrics.
PCI exhibits a boundary effect and generally follows distance decay, with variations in urbanized areas.
The index is a spatiotemporal-continuous and easy-to-implement measurement.

Conclusions:

PCI offers a robust new metric for quantifying place connectivity.
PCI shows significant potential for applications in modeling disease spread (e.g., COVID-19) and human behavior during emergencies (e.g., hurricane evacuations).
The open-sourced PCI datasets and visualization platform will support research on human spatial interactions.