Suicidal Post Detection in Social Networks using NLP

Authors

sentiment analysis, suicide detection, social media, machine learning

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.

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