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

  • Authors
  • Ramírez-Cifuentes, Diana; Freire, Ana
  • UPF authors
  • Type
  • Articles de recerca
  • Journal títle
  • CEUR Workshop Proceedings
  • Publication year
  • 2018
  • Pages
  • 1-12
  • ISSN
  • 1613-0073
  • Publication State
  • Publicat
  • 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.
  • Complete citation
  • Ramírez-Cifuentes, Diana; Freire, Ana. UPF's participation at the CLEF eRisk 2018: early risk prediction on the Internet. CEUR Workshop Proceedings 2018; ( ): 1-12.
Bibliometric indicators
  • Índex Scimago de 0.166(2018)