Psychology

Predicting recurrent chat contact in a psychological intervention for the youth using natural language processing

S. Hornstein, J. Scharfenberger, et al.

This study by Silvan Hornstein, Jonas Scharfenberger, Ulrike Lueken, Richard Wundrack, and Kevin Hilbert explores how Natural Language Processing can predict recurrent chat contacts in a German youth crisis service. With an XGBoost classifier achieving an AUROC of 0.68, the research reveals intriguing insights into the demographics and conditions associated with recontact, highlighting NLP's potential for tailored care in chat-based hotlines.

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