ADHD Twitter users lean toward cognitive, sleep, appetite, and fatigue language in depression-related tweets, while ASD users lean toward anhedonia and suicidal ideation, with shared co-occurrence structure.
Detecting and measuring depression on social media using a machine learning approach: systematic review
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Population-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter: An Exploratory Study Using Advanced NLP and Statistical Analysis
ADHD Twitter users lean toward cognitive, sleep, appetite, and fatigue language in depression-related tweets, while ASD users lean toward anhedonia and suicidal ideation, with shared co-occurrence structure.