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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Main Authors: L. Ermakova, S. Ermakov
Format: Article
Language:English
Published: Ivannikov Institute for System Programming of the Russian Academy of Sciences 2018-10-01
Series:Труды Института системного программирования РАН
Subjects:
Online Access:https://ispranproceedings.elpub.ru/jour/article/view/831
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spelling 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
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