Towards suicide prevention: early detection of depression on social media

Leiva Aranda, Víctor

Towards suicide prevention: early detection of depression on social media

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Citation

Leiva Aranda, V. Towards suicide prevention: early detection of depression on social media. 2017. handle: http://hdl.handle.net/10230/33112

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Abstract

The statistics presented by the World Health Organization inform that 90% of the suicides can be attributed to mental illnesses in high-income countries. Besides, previous studies concluded that people with mental illnesses tend to reveal their mental condition on social media, as a way of relief. Among all these users of social media platforms, adolescents are the most frequent ones. Hence, these previous studies drive us through the detection of depression on social media as a first step against online suicidal behaviour. Thus, the main objective of this work is the analysis of the messages that user posts online, sequentially through a time period, and detect as soon as possible if the user is at risk of depression. Our preliminary experiments report the impact of sentiment analysis techniques and a combination of machine learning algorithms for detecting users with depression in Reddit.