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Published in:
2015 | OriginalPaper | Chapter
Detecting Emotion Stimuli in Emotion-Bearing Sentences
Authors : Diman Ghazi, Diana Inkpen, Stan Szpakowicz
Published in: Computational Linguistics and Intelligent Text Processing
Publisher: Springer International Publishing
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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.