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Detecting Emotion Stimuli in Emotion-Bearing Sentences

  • Conference paper
Computational Linguistics and Intelligent Text Processing (CICLing 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9042))

Abstract

Emotion, a pervasive aspect of human experience, has long been of interest to social and behavioural sciences. It is now the subject of multi-disciplinary research also in computational linguistics. Emotion recognition, studied in the area of sentiment analysis, has focused on detecting the expressed emotion. A related challenging question, why the experiencer feels that emotion, has, to date, received very little attention. The task is difficult and there are no annotated English resources. FrameNet refers to the person, event or state of affairs which evokes the emotional response in the experiencer as emotion stimulus. We automatically build a dataset annotated with both the emotion and the stimulus using FrameNet’s emotions-directed frame. We address the problem as information extraction: we build a CRF learner, a sequential learning model to detect the emotion stimulus spans in emotion-bearing sentences. We show that our model significantly outperforms all the baselines.

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Author information

Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada

    Diman Ghazi, Diana Inkpen & Stan Szpakowicz

Authors
  1. Diman Ghazi
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  2. Diana Inkpen
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  3. Stan Szpakowicz
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Corresponding author

Correspondence to Diman Ghazi .

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Editors and Affiliations

  1. Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico DF, Mexico

    Alexander Gelbukh

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Ghazi, D., Inkpen, D., Szpakowicz, S. (2015). Detecting Emotion Stimuli in Emotion-Bearing Sentences. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9042. Springer, Cham. https://doi.org/10.1007/978-3-319-18117-2_12

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  • DOI: https://doi.org/10.1007/978-3-319-18117-2_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18116-5

  • Online ISBN: 978-3-319-18117-2

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