Modeling Temporal Progression of Emotional Status in Mental Health Forum: A Recurrent Neural Net Approach

• Kishaloy Halder ^[1] ; Lahari Poddar ^[1] ; Min-Yen Kan ^[1]
  1. [1] National University of Singapore

     National University of Singapore

     Singapur

     
• Localización: 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis WASSA 2017: Proceedings of the Workshop / Alexandra Balahur Dobrescu (ed. lit.), Saif M. Mohammad (ed. lit.), Erik van der Goot (ed. lit.), 2017, ISBN 978-1-945626-95-1, págs. 127-135
• Idioma: inglés
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• Resumen

  • Patients turn to Online Health Commu- nities not only for information on spe- cific conditions but also for emotional sup- port. Previous research has indicated that the progression of emotional status can be studied through the linguistic patterns of an individual’s posts. We analyze a real- world dataset from the Mental Health sec- tion of healthboards.com. Estimated from the word usages in their posts, we find that the emotional progress across patients vary widely.

    We study the problem of predicting a pa- tient’s emotional status in the future from her past posts and we propose a Recur- rent Neural Network (RNN) based archi- tecture to address it. We find that the fu- ture emotional status can be predicted with reasonable accuracy given her historical posts and participation features. Our eval- uation results demonstrate the efficacy of our proposed architecture, by outperform- ing state-of-the-art approaches with over 0.13 reduction in Mean Absolute Error.