Abdou Malam, Idriss and Arziki, Mohamed and Nezar Bellazrak, Mohammed and Benamara, Farah
and El Kaidi, Assafa and Es-Saghir, Bouchra and He, Zhaolong and Housni, Mouad and Moriceau, Véronique and Mothe, Josiane and Ramiandrisoa, Faneva
IRIT at e-Risk.
(2017)
In: International Conference of the CLEF Association, CLEF 2017 Labs Working Notes (CLEF 2017), 11 September 2017 - 14 September 2017 (Dublin, Ireland).
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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 138kB |
Official URL: http://ceur-ws.org/Vol-1866/paper_135.pdf
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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| HAL Id: | hal-01912779 |
| Audience (conference): | International conference proceedings |
| Uncontrolled Keywords: | |
| Institution: | French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE) Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE) Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE) Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE) Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE) Other partners > Université Paris-Sud 11 (FRANCE) |
| Laboratory name: | |
| Statistics: | download |
| Deposited On: | 19 Sep 2018 14:41 |
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