Issue

Vol. 5, No. 4, November 2020

Mental Disorder Detection via Social Media Mining using Deep Learning

https://doi.org/10.22219/kinetik.v5i4.1120
Binti Kholifah
Politeknik Elektronika Negeri Surabaya
Iwan Syarif
Politeknik Elektronika Negeri Surabaya
Tessy Badriyah
Politeknik Elektronika Negeri Surabaya

Corresponding Author(s) : Binti Kholifah

bintikholifah@pasca.student.pens.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 5, No. 4, November 2020

Abstract

Due to the imperceptible nature of mental disorders, diagnosing a patient with a mental disorder is a challenging task. Therefore, detection in people with mental disorders can be done by looking at the symptoms they experience. One symptom in patients with mental disorders is solitude. Patients with mental disorders feel indifferent to their environment and mainly focus on their own thoughts and emotions. Therefore, the patient looks for a place that can accommodate his feelings. Twitter is one of the most widely used media in measuring one's personality through everyday statements. The symptoms as suggested by psychologists can be explored more broadly using Natural Languages Processing. The process involves taking a lexicon containing keywords that could indicate symptoms of depression. This study uses five criteria as a measure of mental health in a statement: sentiment, basic emotions, the use of personal pronouns, absolutist words, and negative words. The results show that the use of sentiments, emotions, and negative words in a statement is very influential in determining the level of depression. A depressed person more often uses negative words that indicate his self-despair, prolonged sadness, even suicidal thoughts (e.g. "sadly”, “scared”, “die”, “suicide”). In the classification process, LSTM Deep Learning generates an accuracy of 70.89%; precision of 50.24%; recall 70.89%.

Keywords

Mental Disorder Depression Natural Languange Processing Social Media Mining Computational Linguistic
Kholifah, B., Syarif, I., & Badriyah, T. (2020). Mental Disorder Detection via Social Media Mining using Deep Learning. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 5(4), 309-316. https://doi.org/10.22219/kinetik.v5i4.1120
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