Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques
Social media gives young people a place to voice their difficulties and trade opinions on current events in the digital era. Therefore, it is possible to analyze human behaviour using internet media. However, the illness of mental disorder is common yet often ignored. Social media makes it possible...
Saved in:
Main Author: | |
---|---|
Format: | Undergraduates Project Papers |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/40166/1/CA19033.pdf http://umpir.ump.edu.my/id/eprint/40166/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.ump.umpir.40166 |
---|---|
record_format |
eprints |
spelling |
my.ump.umpir.401662024-02-07T03:46:30Z http://umpir.ump.edu.my/id/eprint/40166/ Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques Lim, Shi Ru QA75 Electronic computers. Computer science Social media gives young people a place to voice their difficulties and trade opinions on current events in the digital era. Therefore, it is possible to analyze human behaviour using internet media. However, the illness of mental disorder is common yet often ignored. Social media makes it possible to identify mental health disorders in large populations. Many efforts have been made to evaluate individual postings using machine learning techniques to identify people with mental health conditions on social media. This study attempted to predict mental health disorders among Twitter users using machine learning techniques. Support Vector Machine (SVM), Decision Tree, and Nave Bayes are three examples of machine learning approaches applied in this study. To assess the algorithms, the performance and accuracy of these three algorithms are compared. 2022-12 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40166/1/CA19033.pdf Lim, Shi Ru (2022) Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques. Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah. |
institution |
Universiti Malaysia Pahang Al-Sultan Abdullah |
building |
UMPSA Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaysia Pahang Al-Sultan Abdullah |
content_source |
UMPSA Institutional Repository |
url_provider |
http://umpir.ump.edu.my/ |
language |
English |
topic |
QA75 Electronic computers. Computer science |
spellingShingle |
QA75 Electronic computers. Computer science Lim, Shi Ru Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques |
description |
Social media gives young people a place to voice their difficulties and trade opinions on current events in the digital era. Therefore, it is possible to analyze human behaviour using internet media. However, the illness of mental disorder is common yet often ignored. Social media makes it possible to identify mental health disorders in large populations. Many efforts have been made to evaluate individual postings using machine learning techniques to identify people with mental health conditions on social media. This study attempted to predict mental health disorders among Twitter users using machine learning techniques. Support Vector Machine (SVM), Decision Tree, and Nave Bayes are three examples of machine learning approaches applied in this study. To assess the algorithms, the performance and accuracy of these three algorithms are compared. |
format |
Undergraduates Project Papers |
author |
Lim, Shi Ru |
author_facet |
Lim, Shi Ru |
author_sort |
Lim, Shi Ru |
title |
Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques |
title_short |
Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques |
title_full |
Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques |
title_fullStr |
Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques |
title_full_unstemmed |
Predicting Mental Health Disorder On Twitter Using Machine Learning Techniques |
title_sort |
predicting mental health disorder on twitter using machine learning techniques |
publishDate |
2022 |
url |
http://umpir.ump.edu.my/id/eprint/40166/1/CA19033.pdf http://umpir.ump.edu.my/id/eprint/40166/ |
_version_ |
1822924120758681600 |
score |
13.23648 |