UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 4 | April 2026

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Published in:

Volume 12 Issue 4
April-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2504311


Registration ID:
558757

Page Number

d69-d75

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Title

Natural Language Processing for Sentiment Analysis in Mental Health Prediction

Abstract

Abstract Disorders such as depression, anxiety, and stress are rapidly becoming one of the world’s most serious problems, affecting society and the economy on a substantial level. Shifts to automatic processes for intervention propose new promising avenues, such as using Neural Language Processing (NLP) to bypass the biases and discrimination inherent in traditional methods. This study investigates the detection of mental health disorders by analyzing user-generated content on platforms such as Twitter, Facebook, and Reddit utilizing sentiment analysis within the framework of natural language processing (NLP). The primary focus is on how effective NLP techniques align text data analytics with mental distress, particularly concerning predicting anxiety and depression. Moreover, the study examines the sentiment-mental health relationship to evaluate the developed early detection models while facing challenges of responsibly integrating these technologies. There is promise in sentiment analysis, but problems such as cultural context, indirect sentiment expression, and privacy issues are still key obstacles. The results demonstrate the transformative potential of NLP technologies for predicting mental health issues in offering proactive support, but further research is necessary to refine the models so they can be implemented accurately and ethically.

Key Words

Natural Language Processing, Sentiment Analysis, Mental Health Prediction, Depression, Anxiety, Social Media, Early Detection, Text Analysis, Machine Learning, Mental Health Disorders, Ethical Considerations, User-Generated Content, AI in Healthcare, Linguistic Markers, Mental Wellness, Digital Communication.

Cite This Article

"Natural Language Processing for Sentiment Analysis in Mental Health Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.d69-d75, April-2025, Available :http://www.jetir.org/papers/JETIR2504311.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Natural Language Processing for Sentiment Analysis in Mental Health Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppd69-d75, April-2025, Available at : http://www.jetir.org/papers/JETIR2504311.pdf

Publication Details

Published Paper ID: JETIR2504311
Registration ID: 558757
Published In: Volume 12 | Issue 4 | Year April-2025
DOI (Digital Object Identifier):
Page No: d69-d75
Country: patiala, punjab, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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