Leiva V, Freire A. Towards suicide prevention: early detection of depression on social media. 4th International Conference on Internet Science (INSCI 2017)

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. Thus, the main objective of this work is the analysis of the messages that a user posts online, sequentially through a time period, and detect as soon as possible if this user is at risk of depression. This paper is a preliminary attempt to minimize measures that penalize the delay in detecting positive cases. Our experiments underline the importance of an exhaustive sentiment analysis and a combination of learning algorithms to detect early symptoms of depression

Addtional material:

• Open access version at UPF e-repository