Harvesting Twitter Data for Studying Motor Behavior in Disabled Populations: An Introduction and Tutorial in Python

Nicholas E. Fears; Riya Chatterjee; Priscila M. Tamplain; Haylie L. Miller

doi:10.1123/jmld.2023-0006

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Harvesting Twitter Data for Studying Motor Behavior in Disabled Populations: An Introduction and Tutorial in Python

Journal article

Peer reviewed

Harvesting Twitter Data for Studying Motor Behavior in Disabled Populations: An Introduction and Tutorial in Python

Nicholas E. Fears, Riya Chatterjee, Priscila M. Tamplain and Haylie L. Miller

Journal of motor learning and development, Vol.11(3), pp.555-570

12/01/2023

DOI: 10.1123/jmld.2023-0006

PMID: 38283882

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Abstract

Social media platforms are rich and dynamic spaces where individuals communicate on a person-to-person level and to broader audiences. These platforms provide a wealth of publicly available data that can shed light on the lived experiences of people from numerous clinical populations. Twitter can be used to examine individual expressions and community discussions about specific characteristics (e.g., motor skills, burnout) associated with a diagnostic group. These data are useful for understanding the perspectives of a diverse, international group of self advocates representing a wide range of clinical populations. Here, we provide a framework for how to harvest data from Twitter through their free, academic researcher application programming interface access using Python, a free, open source programming language. We also provide a sample data set harvested using this framework and a set of analyses on these data specifically related to motor differences in neurodevelopmental conditions. This framework offers a costeffective and flexible means of harvesting and analyzing Twitter data. Researchers should utilize these resources to advance our understanding of the lived experiences of clinical populations through social media platforms and to determine the critical questions that are of most importance to improving quality of life.

Life Sciences & Biomedicine

Psychology

Psychology, Developmental

Psychology, Experimental

Science & Technology

Social Sciences

Sport Sciences

Details

Title: Subtitle: Harvesting Twitter Data for Studying Motor Behavior in Disabled Populations: An Introduction and Tutorial in Python
Creators: Nicholas E. Fears - Louisiana State University
Riya Chatterjee - University of Michigan
Priscila M. Tamplain - The University of Texas at Arlington
Haylie L. Miller - University of Michigan
Resource Type: Journal article
Publication Details: Journal of motor learning and development, Vol.11(3), pp.555-570
DOI: 10.1123/jmld.2023-0006
PMID: 38283882
NLM abbreviation: J Mot Learn Dev
ISSN: 2325-3193
eISSN: 2325-3215
Publisher: Human Kinetics Publ Inc
Number of pages: 16
Grant note: National Institute of Mental Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Mental Health (NIMH) University of Michigan; University of Michigan System
Language: English
Date published: 12/01/2023
Academic Unit: Health, Sport, and Human Physiology
Record Identifier: 9985219850402771

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