Linguistic Approach to Suicide Detection
Suicide is a major, preventable public health problem. Particularly the problem is critical for young people. In Russia every year thousands of teenagers commit suicide. In most of the cases it can be prevented if a risky state is detected. Nowadays internet becomes a major way of communication, mai...
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Ivannikov Institute for System Programming of the Russian Academy of Sciences
2018-10-01
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Online Access: | https://ispranproceedings.elpub.ru/jour/article/view/831 |
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doaj-2e9728fd10f5468cb20760d7f20c3d1c2020-11-25T01:26:04Zeng Ivannikov Institute for System Programming of the Russian Academy of SciencesТруды Института системного программирования РАН2079-81562220-64262018-10-0126411312210.15514/ISPRAS-2014-26(4)-9831Linguistic Approach to Suicide DetectionL. Ermakova0S. Ermakov1Пермский государственный национальный исследовательский университет; Institut de Recherche en Informatique de ToulouseInstitut de Recherche en Informatique de ToulouseSuicide is a major, preventable public health problem. Particularly the problem is critical for young people. In Russia every year thousands of teenagers commit suicide. In most of the cases it can be prevented if a risky state is detected. Nowadays internet becomes a major way of communication, mainly in the text form. Therefore we suggest a method to detect a tendency to suicide based on text messages. Our main approach is to study indicators of such condition and based on it use machine learning approach to build a classifier that could determine, whether the person is about to commit a suicide. Our experiments are based on the analysis of texts of Russian writers for past 100 years that committed suicide.https://ispranproceedings.elpub.ru/jour/article/view/831анализ эмоциональной окраски текстамашинное обучениесуицид |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
L. Ermakova S. Ermakov |
spellingShingle |
L. Ermakova S. Ermakov Linguistic Approach to Suicide Detection Труды Института системного программирования РАН анализ эмоциональной окраски текста машинное обучение суицид |
author_facet |
L. Ermakova S. Ermakov |
author_sort |
L. Ermakova |
title |
Linguistic Approach to Suicide Detection |
title_short |
Linguistic Approach to Suicide Detection |
title_full |
Linguistic Approach to Suicide Detection |
title_fullStr |
Linguistic Approach to Suicide Detection |
title_full_unstemmed |
Linguistic Approach to Suicide Detection |
title_sort |
linguistic approach to suicide detection |
publisher |
Ivannikov Institute for System Programming of the Russian Academy of Sciences |
series |
Труды Института системного программирования РАН |
issn |
2079-8156 2220-6426 |
publishDate |
2018-10-01 |
description |
Suicide is a major, preventable public health problem. Particularly the problem is critical for young people. In Russia every year thousands of teenagers commit suicide. In most of the cases it can be prevented if a risky state is detected. Nowadays internet becomes a major way of communication, mainly in the text form. Therefore we suggest a method to detect a tendency to suicide based on text messages. Our main approach is to study indicators of such condition and based on it use machine learning approach to build a classifier that could determine, whether the person is about to commit a suicide. Our experiments are based on the analysis of texts of Russian writers for past 100 years that committed suicide. |
topic |
анализ эмоциональной окраски текста машинное обучение суицид |
url |
https://ispranproceedings.elpub.ru/jour/article/view/831 |
work_keys_str_mv |
AT lermakova linguisticapproachtosuicidedetection AT sermakov linguisticapproachtosuicidedetection |
_version_ |
1725110951805452288 |