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Proceedings chapter
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English

A Data-Driven Approach for Measuring the Severity of the Signs of Depression using Reddit Posts

Published inProceedings of CLEF (Conference and Labs of the Evaluation Forum) 2019 Working Notes, Editors Cappellato L., Ferro N., Losada D.E., Müller H.
Presented at Lugano, Switzerland, September 9-12, 2019
Collection
  • CEUR Workshop Proceedings; 2380
Publication date2019
Abstract

In response to the CLEF eRisk 2019 shared task on measuring the severity of the signs of depression from threads of user submissions on social media, our team has developed a data-driven, ensemble model approach. Our system leverages word polarities, token extraction via mutual information, keyword expansion and semantic similarities for classifying Reddit posts according to the Beck’s Depression Inventory (BDI). Individual models were combined at the post level by majority voting. The approach achieved a baseline performance for the assessed metrics, including Average Hit Rate and Depression Category Hit Rate, being equivalent to the median system in the limit of one standard deviation.

eng
Keywords
  • Depression severity assessment
  • Social networks
  • Natural language processing
  • Machine learning
Affiliation Not a UNIGE publication
Citation (ISO format)
VAN RIJEN, Paul et al. A Data-Driven Approach for Measuring the Severity of the Signs of Depression using Reddit Posts. In: Proceedings of CLEF (Conference and Labs of the Evaluation Forum) 2019 Working Notes. Lugano, Switzerland. [s.l.] : [s.n.], 2019. (CEUR Workshop Proceedings)
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Proceedings chapter (Published version)
Identifiers
  • PID : unige:159573
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