Using Twitter to Detect Psychological Characteristics of Self-Identified Persons With Autism Spectrum Disorder: A Feasibility Study

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ID: 274214
2019
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Abstract
Background: More than 3.5 million Americans live with autism spectrum disorder (ASD). Major challenges persist in diagnosing ASD as no medical test exists to diagnose this disorder. Digital phenotyping holds promise to guide in the clinical diagnoses and screening of ASD. Objective: This study aims to explore the feasibility of using the Web-based social media platform Twitter to detect psychological and behavioral characteristics of self-identified persons with ASD. Methods: Data from Twitter were retrieved from 152 self-identified users with ASD and 182 randomly selected control users from March 22, 2012 to July 20, 2017. We conducted a between-group comparative textual analysis of tweets about repetitive and obsessive-compulsive behavioral characteristics typically associated with ASD. In addition, common emotional characteristics of persons with ASD, such as fear, paranoia, and anxiety, were examined between groups through textual analysis. Furthermore, we compared the timing of tweets between users with ASD and control users to identify patterns in communication. Results: Users with ASD posted a significantly higher frequency of tweets related to the specific repetitive behavior of counting compared with control users (P
Reference Key
hawkins2019jmirusing Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jared B Hawkins;
Journal JMIR mHealth and uHealth
Year 2019
DOI
doi:10.2196/12264
URL
https://mhealth.jmir.org/2019/2/e12264/
Keywords Keywords not found

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