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Learning from Social Media and Contextualisation

Mothe, Josiane Learning from Social Media and Contextualisation. (2018) In: Dagstuhl Seminar 17301 (2017), 24 July 2017 - 28 July 2017 (Dagstuhl, Germany).

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Social media can be a rich source of information either to extract some trends (models)or peculiarities (weak signals). We focused in this talk on early depression detection from social media posts using machine learning techniques and presented some results. We also proposed to use the same type of model to detect and extract locations from short posts when user localisation is not available. Finally, we mentioned our current work on tweet contextualisation that aims helping users to understand short texts.

Item Type:Conference or Workshop Item (Poster)
Additional Information:Dagstuhl Reports, Vol. 7, Issue 7 (ISSN 2192-5283) : http://drops.dagstuhl.de/opus/volltexte/dagrep-complete/2017/dagrep-v007-i007-complete.pdf
HAL Id:hal-02348226
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (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)
Laboratory name:
Deposited On:16 Oct 2019 09:25

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