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Analyzing GPS Data for Psychological Research: A Tutorial

Year: 2022

Type: article

Abstract: The ubiquity of location-data-enabled devices provides novel avenues for psychology researchers to incorporate spatial analytics into their studies. Spatial analytics use global positioning system (GPS) data to assess and understand mobility behavior (e.g., locations visited, movement patterns). In this tutorial, we provide a practical guide to analyzing GPS data in R and introduce researchers to key procedures and resources for conducting spatial analytics. We show readers how to clean GPS data, compute mobility features (e.g., time spent at home, number of unique places visited), and visualize locations and movement patterns. In addition, we discuss the challenges of ensuring participant privacy and interpreting the psychological implications of mobility behaviors. The tutorial is accompanied by an R Markdown script and a simulated GPS data set made available on the OSF.

Source: Advances in Methods and Practices in Psychological Science

DOI: 10.1177/25152459221082680

Authors: Sandrine R. Müller, Joseph B. Bayer, Morgan Quinn Ross, Jerry Mount, Clemens Stachl, Gabriella M. Harari, Yung-Ju Chang, Huyen T. K. Le

Institutions: Columbia University, The Ohio State University, University of Iowa, University of St.Gallen, Stanford University, National Yang Ming Chiao Tung University

Language: English

Topic: Human Mobility and Location-Based Analysis

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,000

OpenAlex ID: W4293108633

FWCI: 4.195

Cites: 35

Cited by: 29

Related to: 10