Early risk detection of anorexia on social media
Early risk detection of anorexia on social media
Citació
- Ramírez-Cifuentes D, Mayans M, Freire A. Early risk detection of anorexia on social media. In: Bodrunova S, editor. Internet Science. 5th International Conference, INSCI 2018, Proceedings; 2018 Oct 24-26; St. Petersburg, Russia. Cham: Springer; 2018. p. 3-14. (LNCS; no. 11193. LNISA; no. 11193). DOI: 10.1007/978-3-030-01437-7_1
Enllaç permanent
Descripció
Resum
This paper proposes an approach for the early detection of anorexia nervosa (AN) on social media. We present a machine learning approach that processes the texts written by social media users. This method relies on a set of features based on domain-specific vocabulary, topics, psychological processes, and linguistic information extracted from the users’ writings. This approach penalizes the delay in detecting positive cases in order to classify the users in risk as early as possible. Identifying anorexia early, along with an appropriate treatment, improves the speed of recovery and the likelihood of staying free of the illness. The results of this work showed that our proposal is suitable for the early detection of AN symptoms.Descripció
Comunicació presentada a: INSCI 2018 celebrada del 24 al 26 d'octubre de 2018 a Sant Petersburg, Rússia.