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IRIT at e-Risk

Abstract : In this paper, we present the method we developed when participating to the e-Risk pilot task. We use machine learning in order to solve the problem of early detection of depressive users in social media relying on various features that we detail in this paper. We submitted 4 models which differences are also detailed in this paper. Best results were obtained when using a combination of lexical and statistical features.
Keywords : e-Risk
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Submitted on : Monday, November 5, 2018 - 4:39:17 PM
Last modification on : Wednesday, September 16, 2020 - 5:30:50 PM
Long-term archiving on: : Wednesday, February 6, 2019 - 4:07:30 PM


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  • HAL Id : hal-01912779, version 1
  • OATAO : 19082


Idriss Abdou Malam, Mohamed Arziki, Mohammed Nezar Bellazrak, Farah Benamara, Assafa El Kaidi, et al.. IRIT at e-Risk. International Conference of the CLEF Association, CLEF 2017 Labs Working Notes (CLEF 2017), Sep 2017, Dublin, Ireland. pp. 1-7. ⟨hal-01912779⟩



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