IRIT at e-Risk - Archive ouverte HAL Access content directly
Conference Papers Year : 2017

IRIT at e-Risk


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.


Fichier principal
Vignette du fichier
abdoumalam_19082.pdf (135.51 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-01912779 , version 1 (05-11-2018)



  • 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. 8th International Conference of the CLEF Association (CLEF 2017), Sep 2017, Dublin, Ireland. pp.1-7. ⟨hal-01912779⟩
144 View
79 Download


Gmail Mastodon Facebook X LinkedIn More