Survival analysis of three years of X posts shows conspiracy claims with greater semantic mutations have substantially longer lifespans, linked to changes in pronouns, social words, cognitive terms, and actor-action-target structures.
The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods
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Transformer-derived sentiment features from therapy sessions correlate with emotional-valence components of the OQ-45 and differ significantly between patients identified as at risk of deterioration by rational and empirical outcome models.
Ultra-brief student concern texts analyzed with NLP associate with lower physical activity during academic concern weeks and poorer sleep plus lower heart rate variability during emotional exhaustion weeks, complementing wearable sensing.
Finetuning GPT-1 on 150000 unlabeled Reachout.com posts then feeding the features into AutoML yields a new state-of-the-art macro F1 of 0.572 for triaging risk in 1588 labeled CLPsych 2017 posts without metadata or history.
citing papers explorer
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Language Mutations Sustain the Persistences of Conspiracy Theories on Social Media
Survival analysis of three years of X posts shows conspiracy claims with greater semantic mutations have substantially longer lifespans, linked to changes in pronouns, social words, cognitive terms, and actor-action-target structures.
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The Association of Transformer-based Sentiment Analysis with Symptom Distress and Deterioration in Routine Psychotherapy Care
Transformer-derived sentiment features from therapy sessions correlate with emotional-valence components of the OQ-45 and differ significantly between patients identified as at risk of deterioration by rational and empirical outcome models.
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A Formative Study of Brief Affective Text as a Complement to Wearable Sensing for Longitudinal Student Health Monitoring
Ultra-brief student concern texts analyzed with NLP associate with lower physical activity during academic concern weeks and poorer sleep plus lower heart rate variability during emotional exhaustion weeks, complementing wearable sensing.
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Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation Study
Finetuning GPT-1 on 150000 unlabeled Reachout.com posts then feeding the features into AutoML yields a new state-of-the-art macro F1 of 0.572 for triaging risk in 1588 labeled CLPsych 2017 posts without metadata or history.