AI model predicts suicidal ideation from adolescent social media posts

Researchers have developed a novel transformer-based model called Early-SIB to predict future suicidal ideation and behavior (SIB) by analyzing adolescent social media posts. The model achieved a balanced accuracy of 0.73 in predicting SIB on a Dutch youth forum, demonstrating its potential to supplement traditional risk assessment methods. Interpretability was enhanced using Shapley Additive Explanations to understand the model's predictions. AI

IMPACT Could offer a new tool for early detection of mental health crises, complementing traditional methods.

RANK_REASON Academic paper detailing a new model and its performance on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

• adolescent social media texts
• alphaXiv
• arXiv
• CatalyzeX
• DagsHub
• Dutch youth forum
• Enrico Liscio
• Gotit.pub
• Hugging Face
• ScienceCast
• Shapley Additive Explanations
• suicidal ideation and behavior (SIB)
• transformer-based model

• paper
• safety
• product

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