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Analysis of Social Media Posts for Early Detection of Mental Health Conditions

  • Antoine Briand
  • Hayda Almeida
  • Marie-Jean Meurs
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10832)

Abstract

This paper presents a multipronged approach to predict early risk of mental health issues from user-generated content in social media. Supervised learning and information retrieval methods are used to estimate the risk of depression for a user given the content of its posts in reddit. The approach presented here was evaluated on the CLEF eRisk 2017 pilot task. We describe the details of five systems submitted to the task, and compare their performance. The comparisons show that combining information retrieval and machine learning methods gives the best results.

Keywords

Artificial intelligence Classification Information retrieval Machine learning Mental health Natural language processing Social media Text mining 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Antoine Briand
    • 1
  • Hayda Almeida
    • 1
  • Marie-Jean Meurs
    • 1
  1. 1.Université du Québec à MontréalMontréalCanada

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