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Using of Natural Language Processing Techniques in Suicide Research

Azam Orooji, Mostafa Langarizadeh

Abstract


It is estimated that each year many people, most of whom are teenagers and young adults die by suicide worldwide. Suicide receives special attention with many countries developing national strategies for prevention. Since, more medical information is available in text, Preventing the growing trend of suicide in communities requires analyzing various textual resources, such as patient records, information on the web or questionnaires. For this purpose, this study systematically reviews recent studies related to the use of natural language processing techniques in the area of people’s health who have completed suicide or are at risk. After electronically searching for the PubMed and ScienceDirect databases and studying articles by two reviewers, 21 articles matched the inclusion criteria. This study revealed that, if a suitable data set is available, natural language processing techniques are well suited for various types of suicide related research.

Keywords


Natural Language Processing (NLP); Information Extraction (IE); Text Mining; Machine Learning; Information Retrieval.

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DOI: 10.28991/esj-2017-01120

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Copyright (c) 2017 Azam Orooji, Mostafa Langarizadeh