Towards suicide prevention: early detection of depression on social media

Leiva, Víctor; Freire, Ana

doi:http://dx.doi.org/10.1007/978-3-319-70284-1_34

Towards suicide prevention: early detection of depression on social media

Citation

Leiva V, Freire A. Towards suicide prevention: early detection of depression on social media. In: Kompatsiaris I, Cave J, Satsiou A, Carle G, Passani A, Kontopoulos E, Diplaris S, McMillan D, editors. Internet Science: 4th International Conference, INSCI 2017, Thessaloniki, Greece, November 22-24, 2017, Proceedings. [Germany]: Springer, 2017. p. 428-36. (LNCS; no. 10673). DOI: 10.1007/978-3-319-70284-1_34

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. 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.