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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| Format: | Final Year Project Report |
| Language: | English |
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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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my.unimas.ir.340412024-01-11T01:47:44Z http://ir.unimas.my/id/eprint/34041/ SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING Heng, Elvin Jia Guang QA76 Computer software 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. Universiti Malaysia Sarawak (UNIMAS) 2020 Final Year Project Report NonPeerReviewed text en http://ir.unimas.my/id/eprint/34041/4/Elvin%20Heng%20JG.pdf Heng, Elvin Jia Guang (2020) SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING. [Final Year Project Report] (Unpublished) |
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| language |
English |
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QA76 Computer software |
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QA76 Computer software Heng, Elvin Jia Guang SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING |
| description |
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. |
| format |
Final Year Project Report |
| author |
Heng, Elvin Jia Guang |
| author_facet |
Heng, Elvin Jia Guang |
| author_sort |
Heng, Elvin Jia Guang |
| title |
SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING |
| title_short |
SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING |
| title_full |
SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING |
| title_fullStr |
SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING |
| title_full_unstemmed |
SUICIDAL TENDENCY DETECTION USING MACHINE LEARNING |
| title_sort |
suicidal tendency detection using machine learning |
| publisher |
Universiti Malaysia Sarawak (UNIMAS) |
| publishDate |
2020 |
| url |
http://ir.unimas.my/id/eprint/34041/4/Elvin%20Heng%20JG.pdf http://ir.unimas.my/id/eprint/34041/ |
| _version_ |
1789430322119573504 |
| score |
13.209306 |