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.
- Diana Ramírez-Cifuentes, Ana Freire et al. "Detection of suicidal ideation on social media: multimodal, relational, and behavioral analysis." Journal of medical internet research 22.7 (2020): e17758. JCR: 5.03. Q1.
- Ríssola, Esteban, Diana Ramírez-Cifuentes, Ana Freire, and Fabio Crestani. "Suicide risk assessment on social media: USI-UPF at the CLPsych 2019 shared task." In Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, pp. 167-171. 2019.
- Diana Ramírez-Cifuentes, Marc Mayans and Ana Freire. Early Risk Detection of Anorexia in Social Media. In Proc. of INSCI 2018 - International Conference on Internet Science. 2018. SJR 0.29. Q2.
- Diana Ramírez-Cifuentes and Ana Freire. UPF's Participation at the CLEF eRisk 2018: Early Risk Prediction on the Internet. Conference and Labs of the Evaluation Forum. CLEF 2018.
- Ana Freire, Joaquim Puntí-Vidal, Montserrat Pàmias-Massana and Michele Trevisiol. Suicide 2.0: Tracking Online Symptoms to Detect Suicidal Behaviour. Salut Mental 4.0. Les noves tecnologies aplicades a la recerca i tractament en Salut Mental. Quart Seminari de la CORE en Salut Mental. 2017.
Website of the project (More information and complete list of publications)