Description

According to a recent report by the World Health Organization, there is 1 in every 8 people in the world suffering from a mental disorder. The COVID-19 pandemic has raised the prevalence of anxiety and depression to more than 26% in just one year. Suicide is the fourth leading cause of death among 15-29 year-olds. The organisation considers that early identification is a key effective intervention to prevent these problems.

Consequently, there is a growing interest in detecting and identifying mental disorders in social media streams. This answers a demand from society due to the high increase in these problems among the population, in several kinds of mental risks: eating disorders, dysthymia, anxiety, depression, suicidal ideation, and others. Actually, relevant evaluation campaigns like the Cross-Lingual Evaluation Forum (CLEF)  have hosted during the last years the Early-Risk Identification task (eRisk). Unfortunately, these campaigns have focused mainly on English, leaving aside other languages, like Spanish. 

MentalRiskEs is a novel task on early risk identification of mental disorders in Spanish comments from Telegram users. The task must be resolved as an online problem, that is, the participants must be able to detect a potential risk as early as possible in a continuous stream of data. Therefore, the performance not only depends on the accuracy of the systems but also on how fast the problem is detected. These dynamics are reflected in the design of the tasks and the metrics used to evaluate participants. For this first edition, the disorders considered are eating disorders, depression, and an unknown one which is intended to evaluate the robustness of approaches for new disorders not known a priori.

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