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UPF’s participation at the CLEF eRisk 2018: early risk prediction on the Internet

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dc.contributor.author Ramíırez-Cifuentes, Diana
dc.contributor.author Freire, Ana
dc.date.accessioned 2018-10-09T14:43:56Z
dc.date.available 2018-10-09T14:43:56Z
dc.date.issued 2018
dc.identifier.citation Ramírez-Cifuentes D, Freire A. UPF’s participation at the CLEF eRisk 2018: early risk prediction on the Internet. In. Cappellato L, Ferro N, Nie JY, Soulier L, editors. Working Notes of CLEF 2018 - Conference and Labs of the Evaluation Forum; 2018 Sep 10-14; Avignon, France. [Avignon]: CEUR Workshop Proceedings; 2018. p. 1-12.
dc.identifier.issn 1613-0073
dc.identifier.uri http://hdl.handle.net/10230/35589
dc.description.abstract This paper describes the participation of the Web Science and Social Computing Research Group from the Universitat Pompeu Fabra, Barcelona (UPF) at CLEF 2018 eRisk Lab1. Its main goal, di- vided in two different tasks, is to detect, with enough anticipation, cases of depression (T1) and anorexia (T2) given a labeled dataset with texts written by social media users. Identifying depressed and anorexic indi- viduals by using automatic early detection methods, can provide experts a tool to do further research regarding these conditions, and help people living with them. Our proposal presents several machine learning models that rely on features based on linguistic information, domain-specific vo- cabulary and psychological processes. The results, regarding the F-Score, place our best models among the top 5 approaches for both tasks.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher CEUR Workshop Proceedings
dc.relation.ispartof Cappellato L, Ferro N, Nie JY, Soulier L, editors. Working Notes of CLEF 2018 - Conference and Labs of the Evaluation Forum; 2018 Sep 10-14; Avignon, France. [Avignon]: CEUR Workshop Proceedings; 2018. p. 1-12.
dc.rights Copyright © 2018 the authors.
dc.rights.uri https://creativecommons.org/licenses/by/3.0/es/
dc.title UPF’s participation at the CLEF eRisk 2018: early risk prediction on the Internet
dc.type info:eu-repo/semantics/article
dc.subject.keyword Early risk detection
dc.subject.keyword Social media
dc.subject.keyword Depression
dc.subject.keyword Anorexia
dc.subject.keyword Machine learning
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/642563
dc.relation.projectID This work was supported by the Spanish Ministry of Economy and Competitive- ness under the Maria de Maeztu Units of Excellence Programme (MDM-2015- 0502).
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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