Predicting mental health disorder on twitter using machine learning techniques

Lim, Shi Ru and Nur Shazwani, Kamarudin and Nur Hafieza, Ismail and Nik Ahmad, Hisham Ismail and Nor Ashikin, Mohamad Kamal (2023) Predicting mental health disorder on twitter using machine learning techniques. In: 8th International Conference on Software Engineering and Computer Systems, ICSECS 2023 , 25-27 August 2023 , Penang. pp. 23-27. (192961). ISBN 979-835031093-1

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Abstract

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 behavior 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 Naive 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.

Item Type:	Conference or Workshop Item (Lecture)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Accuracy; Machine learning; Mental health; Prediction; Twitter
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Faculty/Division:	Faculty of Computing
Depositing User:	Mr Muhamad Firdaus Janih@Jaini
Date Deposited:	16 Apr 2024 04:12
Last Modified:	16 Apr 2024 04:12
URI:	http://umpir.ump.edu.my/id/eprint/40339
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