Detecting Traces of Self-harm in Social Media: A Simple and Interpretable Approach

Author:

Aguilera Juan,Farías Delia Irazú HernándezORCID,Montes-y-Gómez ManuelORCID,González Luis C.ORCID

Publisher

Springer International Publishing

Reference22 articles.

1. Aguilera, J., González, L.C., Montes-y-Gómez, M., López, R., Escalante, H.J.: From neighbors to strengths - the k-strongest strengths (kSS) classification algorithm. Pattern Recogn. Lett. 136, 301–308 (2020)

2. Aguilera, J., Hernández Farías, D.I., Ortega-Mendoza, R.M., Montes-y Gómez, M.: Depression and anorexia detection in social media as a one-class classification problem. Appl. Intell. 1–16 (2021)

3. Alhassan, M.A., Inuwa-Dutse, I., Bello, B.S., Pennington, D.R.: Self-harm: detection and support on twitter. CoRR abs/2104.00174 (2021)

4. Aragón, M., López-Monroy, A.P., y Gómez, M.M.: INAOE-CIMAT at eRisk 2020: detecting signs of self-harm using sub-emotions and words. In: CLEF (2020)

5. Baumgartner, J., Zannettou, S., Keegan, B., Squire, M., Blackburn, J.: The pushshift reddit dataset. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 14, no. 1, pp. 830–839 (2020)

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