September 5, 2025International Journal for Research in Applied Science and Engineering TechnologyOpen Access

AI and NLP for Mental Health Prediction from Social Media: A Decade of Progress, Challenges, and Explainability (2015–2025)

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AI and NLP methods enhance mental health prediction from social media, with deep learning showing significant improvements.
Dataset analysis reveals a heavy reliance on Reddit for data collection, accounting for nearly 60% of sources in this field.
Explainable AI techniques, such as SHAP and LIME, are essential for enhancing model interpretability yet remain underexplored, particularly in non-English contexts.
Challenges like bias and computational costs still exist, signaling a need for more inclusive datasets and efficient models in future research.

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Implication

This review highlights the evolution of AI and NLP methods for mental health prediction from social media data, indicating challenges in explainability.

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Thakur et al. (2025) studied this question.

synapsesocial.com/papers/68c238d2b210217d64779cf6 https://doi.org/10.22214/ijraset.2025.73857

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Implication

This review highlights the evolution of AI and NLP methods for mental health prediction from social media data, indicating challenges in explainability.

AI and NLP for Mental Health Prediction from Social Media: A Decade of Progress, Challenges, and Explainability (2015–2025)

Key Points

Discussion

Implication

Cite This Study

AI and NLP for Mental Health Prediction from Social Media: A Decade of Progress, Challenges, and Explainability (2015–2025)

Key Points

Discussion

Implication

Cite This Study

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