CLPsych
@CLPsychOrg
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Computational Linguistics and Clinical Psychology Workshop
Joined March 2017
CLPsych 2025 is happening 🎉 and will be collocated with NAACL. The first Call for Papers is out. Please consider submitting and help us spread the word.
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CLPsych 2025 shared task registration is now open -- deadline is February 9th. We hope you can participate!
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We are extending the submission deadline of CLPsych 2025 to February 16th. Please submit via
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Deadline is coming soon to submit your amazing work to CLPsych (end of January) via softconf
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Deadline Extension!!! CLPsych 2024 is accepting papers till December 22nd 11:59pm AoE
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RT @adtsakal: 📢CLPsych Shared Task '24 🗓️Registration deadline: December 10th ℹ️If you are interested in working with LLMs for "explaining…
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CLPsych 2024 is collocated with EACL and the first CFP is out. We are looking forward to seeing your submissions
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Yaara Shriki and colleagues in "Masking Morphosyntactic Categories to Evaluate Salience for Schizophrenia Diagnosis" fine-tune a language model and mask nouns, verbs and some other morphosyntactic categories to detect transcribed speech of patients diagnosed with schizophrenia
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Daeun Lee et al. developed the suicidality detection model C-GraphSAGE based on a graph neural network to grasp the dynamic semantic information of social media post by using the suicide vocabulary efficiently.
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Check out shared task paper "Multi-Task Learning to Capture Changes in Mood Over Time". The authors investigate the impact of using MTL to predict mood changes over time of social media users --From: uOttawa-AI
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To what extent do people who engage in non-suicidal self-injury conceptualize their behavior as an addiction? Using #reddit data we identify shared language across #NSSI and #SubstanceUse Reddits, showing borrowed #recovery language when describing self-harm
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Neural networks can extract emotions from online therapy messages and predict depression and anxiety, a work by Hannah Burkhardt and colleagues at CLPsych.
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Check out shared task paper by John Culnan et al. where authors used RoBERTa-based models and a feature representing time between posts to model changes in mood over time in Reddit posts.
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What is Linguistic Synchrony? How can it be measured? And what is it good for? Work by Natalie Shapira et al. "Measuring Linguistic Synchrony in Psychotherapy" at CLPsych
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How are language-based predictions of psychological factors associated with more frequent mood changes? Check out the work from @WWBProject at #CLPsych to learn interesting associations, and about how transformer-based models track mental health signals over time. #NAACL2022
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The relationship between multiple mental health conditions are explorable and exploitable. To learn more check the work "Are You Really Okay? A Transfer Learning-based Approach for Identification of Underlying Mental Illnesses" by @ankitaich30 and colleagues
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@MashruraTasnim @Malikeh5 @Brian13Diep @J_Novikova_NLP introduced DEPAC, a high-quality corpus with 2500+ speech samples and 500+ hand-curated features for detecting depression and anxiety. Baseline ML models trained on DEPAC show promise for depression severity prediction.
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How to build more explainable depression detection models that the clinicians want to use? Check @AyaZirikly @mdredze work on how using PHQ-9 auxiliary models can better explain depression detection models @jhuclsp
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Check out the shared task poster by Ana-Maria Bucur et al. on capturing changes in mood over time in longitudinal data using ensemble methodologies
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