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Erschienen in:
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2020 | OriginalPaper | Buchkapitel

Artificial Intelligence in Detecting Suicidal Content on Russian-Language Social Networks

verfasst von : Sergazy Narynov, Kanat Kozhakhmet, Daniyar Mukhtarkhanuly, Aizhan Sambetbayeva, Batyrkhan Omarov

Erschienen in: Advances in Computational Collective Intelligence

Verlag: Springer International Publishing

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Abstract

Due to the anonymity of online media and social networks, people tend to Express their feelings and suffering in online communities. To prevent suicides, it is necessary to detect messages about suicides and user perceptions of suicides in cyberspace using natural language processing methods. We focus on the social network Vkontakte and classify users’ messages with potential suicide and without suicidal risk using text processing and machine learning methods.
In this paper, we tell about suicidal and depressive ideation detection in Russian Language. For this purpose, we create a dataset that consists of 64,000 posts that collected from Russian language social network Vkontakte. The dataset was applied to eight machine learning algorithms.

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Vorheriges Kapitel Textual Clustering: Towards a More Efficient Descriptors of Texts
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Metadaten
Titel
Artificial Intelligence in Detecting Suicidal Content on Russian-Language Social Networks
verfasst von
Sergazy Narynov
Kanat Kozhakhmet
Daniyar Mukhtarkhanuly
Aizhan Sambetbayeva
Batyrkhan Omarov
Copyright-Jahr
2020
Buch
Advances in Computational Collective Intelligence

Print ISBN: 978-3-030-63118-5

Electronic ISBN: 978-3-030-63119-2

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-63119-2_66