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eRisk 2020: autolesiones y desafíos de la depresión

Authors: Losada, David E.; Crestani, Fabio; Parapar, Javier;

eRisk 2020: autolesiones y desafíos de la depresión

Abstract

[Abstract] This paper describes eRisk, the CLEF lab on early risk prediction on the Internet. eRisk started in 2017 as an attempt to set the experimental foundations of early risk detection. Over the last three editions of eRisk (2017, 2018 and 2019), the lab organized a number of early risk detection challenges oriented to the problems of detecting depression, anorexia and self-harm. We review in this paper the main lessons learned from the past and we discuss our future plans for the 2020 edition. We thank the support obtained from the Swiss National Science Foundation (SNSF) under the project “Early risk prediction on the Internet: an evaluation corpus”, 2015. We also thank the financial support obtained from the (i) “Ministerio de Ciencia, Innovación y Universidades” of the Government of Spain (research grants RTI2018-093336-B-C21 and RTI2018-093336-B-C22), (ii) “Consellería de Educación, Universidade e Formación Profesional”, Xunta de Galicia (grants ED431C 2018/29, ED431G/08 and ED431G/01 – “Centro singular de investigación de Galicia” –). All grants were co-funded by the European Regional Development Fund (ERDF/FEDER program) Xunta de Galicia; ED431C 2018/29 Xunta de Galicia; ED431G/08 Xunta de Galicia; ED431G/01

Keywords

Depression, Self-harm, eRisk, Anorexia

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green