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 ...
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.
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