Detection of Mental illness from social media Text

This project aims how social media impacts on mental health, specifically focusing on depression, anxiety, and borderline personality disorder (BPD). A massive dataset from Reddit posts was used it was available in kaggel for download and to analyze signs of these mental health issues. Using various...

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Bibliographic Details
Published in2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) pp. 1 - 6
Main Authors Chandu, Janakiram, Dhanush, Svs, Rohith, D, Kumar, Tsaliki Satya Ganesh, Soman, Kp, Sachin Kumar, S
Format Conference Proceeding
LanguageEnglish
Published IEEE 24.06.2024
Subjects
Anxiety disorders
Borderline personality disorder
Depression
Forestry
Global Vectors for Word Representation
K-Nearest Neighbors
Knowledge engineering
Mental health
Natural languages
Random Forest
Social networking (online)
Transformers
Vectors
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Summary:This project aims how social media impacts on mental health, specifically focusing on depression, anxiety, and borderline personality disorder (BPD). A massive dataset from Reddit posts was used it was available in kaggel for download and to analyze signs of these mental health issues. Using various computational techniques like Natural Language Processing(NLP), machine learning(ML), deep learning(DL) and transformers we dug deep into the data to uncover meaningful insights. our initial literature study indicate a concerning trend on many social media users seem to be struggling with feelings of depression and anxiety. This highlights the need for proactive measures to promote healthier online behavior and support mental well-being. Understanding these patterns is crucial for developing effective intervention strategies and advancing our knowledge in computer science and engineering.
ISSN:2473-7674
DOI:10.1109/ICCCNT61001.2024.10725304