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

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• dc.contributor.author Ramíırez-Cifuentes, Dianaca
• dc.contributor.author Freire, Anaca
• dc.date.accessioned 2018-10-09T14:43:56Z
• dc.date.available 2018-10-09T14:43:56Z
• dc.date.issued 2018
• 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.en
• dc.format.mimetype application/pdf
• 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.language.iso eng
• dc.publisher CEUR Workshop Proceedingsca
• 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.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).en
• dc.rights Copyright © 2018 the authors.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/3.0/es/
• dc.subject.keyword Early risk detectionen
• dc.subject.keyword Social mediaen
• dc.subject.keyword Depressionen
• dc.subject.keyword Anorexiaen
• dc.subject.keyword Machine learningen
• dc.title UPF’s participation at the CLEF eRisk 2018: early risk prediction on the Internetca
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion