ANALYZING EMOTIONAL PATTERNS IN SOCIAL MEDIA FOR MENTAL HEALTH DISORDER DETECTION

MEDISETTY ANUSHA; YENUMULA JESSY KUMARI; KAPU NAGESWARA RAO

doi:10.36948/ijfmr.2025.v07i03.47288

ANALYZING EMOTIONAL PATTERNS IN SOCIAL MEDIA FOR MENTAL HEALTH DISORDER DETECTION

Author(s)	Mrs MEDISETTY ANUSHA, Mrs YENUMULA JESSY KUMARI, Dr. KAPU NAGESWARA RAO
Country	India
Abstract	Mental health disorders including depression and anorexia still afflict millions of people globally; their symptoms are often overlooked as they are so subtle and distinctive. Early detection—which is still rather challenging—is what makes effective intervention possible. Social media channels give a rare opportunity to see people's emotional reactions in real time via their written works. This work investigates the emotional patterns in user posts using Natural Language Processing (NLP) methods in search of potential markers of mental health problems. We propose a computational framework including sentiment polarity, emotional categories, and language cues to detect emotional aspects in user-generated social media content. Then trained using these traits a Decision Tree classifier selected for its simplicity of use, interpretability, and feature-based decision making capabilities. Decision trees help to successfully distinguish between impacted and non-affected persons by use of emotional-based attributes. Two public ally datasets related to depression and anorexia are used for testing the algorithm. Thanks to the interpretable structure of decision trees, our approach provides better transparency; it also achieves competitive performance quite similar to state-of-the-art models. Apart from raising detection accuracy, the coupling of decision tree classification with NLP-driven emotional analysis generates chances for explainable artificial intelligence in applications related to mental health. This method prepares the stage for real-time, non-invasive support systems emphasizing early mental health care detection and intervention.
Keywords	Mental Health Detection, Natural Language Processing (NLP), Emotional Pattern Recognition, Decision Tree Classifier, Depression, Interpretable Machine Learning, Early Intervention
Field	Engineering
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-06-28
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.47288
Short DOI	https://doi.org/g9rnxj

View / Download PDF File

E-ISSN 2582-2160

doi

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads

Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 3 Cover Page Vol 7 Isu 2 Cover Page Vol 7 Isu 1

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

ANALYZING EMOTIONAL PATTERNS IN SOCIAL MEDIA FOR MENTAL HEALTH DISORDER DETECTION

Share this