Suicide prevenTion in sOcial Platforms
Suicide risk assessment usually involves an interaction between doctors and patients. However, a significant number of people with mental disorders receive no treatment for their condition due to the limited access to mental health care facilities; the reduced availability of clinicians; the lack of awareness; and stigma, neglect, and discrimination surrounding mental disorders. In contrast, internet access and social media usage have increased significantly, providing experts and patients with a means of communication that may contribute to the development of methods to detect mental health issues among social media users.
The objective of this project is to apply Artificial Intelligence on social media data to discover suicide-related patters: suicide ideation, depression, eating disorders. We explore behavioral, relational, and multimodal data extracted from social media and develop machine learning models to detect risk patters. All our data is anonymized to protect the privacy of the users.
Project funded by the Maria de Maetzu Program of the Spanish Government.
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