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200329

Suicidal Post Detection in Social Networks using NLP

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Last updated: 23 Jan 2023

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Abstract

The social problem of suicide and alcoholism among youth is one of the problems, that the government currently faces. According to statistics, Kazakhstan is in the top 10 in the world in teenage suicide and alcoholism rates, as well as in several other social problems. An important stimulus in creating the aforementioned information system (IS) are the global trends in sociology, those focused on research of people with the use of internet technologies. The main methodology used for the development of the IS, is the content analysis of incoming data, because text(oral and written) reflects individual characteristics of a person like a fingerprint, as well as voice characteristics (frequency of vowels, tone, etc.), this allows for the creation of sophisticated analytics, control of psychological stability and observation of mood changes in youth. For this approach various prepossessing methods and machine learning algorithms were used.

DOI

10.21608/aeta.2018.200329

Keywords

Sentiment Analysis, suicide detection, social media, Machine Learning

Authors

First Name

Mukhtarkhanuly

Last Name

Daniyar

MiddleName

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Affiliation

Suleyman Demirel University, Almaty, Kazakhstan

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Orcid

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First Name

Alan

Last Name

Abishev

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Affiliation

Suleyman Demirel University, Almaty, Kazakhstan

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Orcid

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Volume

7

Article Issue

3

Related Issue

28263

Issue Date

2018-09-01

Receive Date

2021-10-19

Publish Date

2018-09-01

Page Start

1

Page End

4

Print ISSN

2090-9535

Online ISSN

2090-9543

Link

https://aeta.journals.ekb.eg/article_200329.html

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https://aeta.journals.ekb.eg/service?article_code=200329

Order

200,329

Type

Original Article

Type Code

2,017

Publication Type

Journal

Publication Title

Advanced Engineering Technology and Application

Publication Link

https://aeta.journals.ekb.eg/

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Article

Created At

23 Jan 2023