SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING
Suicide is a serious mental health problem which has taken away many lives. With the emergence of social media, people are expressing their feelings on social media. Some of them contain negative feelings which are indicative of suicide ideation. This presents a good opportunity to detect suicidal...
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| Main Author: | |
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| Format: | Final Year Project Report |
| Language: | English |
| Published: |
Universiti Malaysia Sarawak (UNIMAS)
2020
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| Online Access: | http://ir.unimas.my/id/eprint/34041/4/Elvin%20Heng%20JG.pdf http://ir.unimas.my/id/eprint/34041/ |
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| Summary: | Suicide is a serious mental health problem which has taken away many lives. With the emergence of social media, people are expressing their feelings on social media. Some of them contain negative feelings which are indicative of suicide ideation. This presents a good
opportunity to detect suicidal tendency from written text, and with early detection and intervention, more lives could be saved. This project aims to apply machine learning techniques to detect suicidal tendency from written text. Several machine learning algorithms and feature engineering techniques are studied and experimented to find out how they perform on the task
of classifying texts into suicidal or non-suicidal texts. |
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