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Mining Twitter for Suicide Prevention

  • Amayas Abboute
  • Yasser Boudjeriou
  • Gilles Entringer
  • Jérôme Azé
  • Sandra Bringay
  • Pascal Poncelet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8455)

Abstract

Automatically detect suicidal people in social networks is a real social issue. In France, suicide attempt is an economic burden with strong socio-economic consequences. In this paper, we describe a complete process to automatically collect suspect tweets according to a vocabulary of topics suicidal persons are used to talk. We automatically capture tweets indicating suicidal risky behaviour based on simple classification methods. An interface for psychiatrists has been implemented to enable them to consult suspect tweets and profiles associated with these tweets. The method has been validated on real datasets. The early feedback of psychiatrists is encouraging and allow to consider a personalised response according to the estimated level of risk.

Keywords

Classification Suicide Tweets 

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References

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Amayas Abboute
    • 1
  • Yasser Boudjeriou
    • 1
  • Gilles Entringer
    • 1
  • Jérôme Azé
    • 1
  • Sandra Bringay
    • 1
    • 2
  • Pascal Poncelet
    • 1
  1. 1.LIRMM UMR 5506, CNRSUniversity of Montpellier 2MontpellierFrance
  2. 2.AMISUniversity of Montpellier 3MontpellierFrance

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