Language of ADHD in Adults on Social Media.
J Atten Disord. 2017 Nov 01;:1087054717738083
Authors: Guntuku SC, Ramsay JR, Merchant RM, Ungar LH
OBJECTIVE: We computationally analyze the language of social media users diagnosed with ADHD to understand what they talk about, and how their language is correlated with users’ characteristics such as personality and temporal orientation.
METHOD: We analyzed approximately 1.3 million tweets written by 1,399 Twitter users with self-reported diagnoses of ADHD, comparing their posts with those used by a control set matched by age, gender, and period of activity.
RESULTS: Users with ADHD are found to be less agreeable, more open, to post more often, and to use more negations, hedging, and swear words. Posts are suggestive of themes of emotional dysregulation, self-criticism, substance abuse, and exhaustion. A machine learning model can predict which of these Twitter users has ADHD with an out-of-sample AUC of .836.
CONCLUSION: Based on this emerging technology, conjectures of future uses of social media by researchers and clinicians to better understand the naturalistic manifestations and sequelae of ADHD.
PMID: 29115168 [PubMed – as supplied by publisher]