An ensemble approach for emotion cause detection with event extraction and multi-kernel SVMs

Ruifeng Xu, Jiannan Hu, Qin Lu, Dongyin Wu, Lin Gui

Research output: Journal article publicationJournal articleAcademic researchpeer-review

40 Citations (Scopus)


In this paper, we present a new challenging task for emotion analysis, namely emotion cause extraction. In this task, we focus on the detection of emotion cause a.k.a the reason or the stimulant of an emotion, rather than the regular emotion classification or emotion component extraction. Since there is no open dataset for this task available, we first designed and annotated an emotion cause dataset which follows the scheme of W3C Emotion Markup Language. We then present an emotion cause detection method by using event extraction framework, where a tree structure-based representation method is used to represent the events. Since the distribution of events is imbalanced in the training data, we propose an under-sampling-based bagging algorithm to solve this problem. Even with a limited training set, the proposed approach may still extract sufficient features for analysis by a bagging of multi-kernel based SVMs method. Evaluations show that our approach achieves an F-measure 7.04% higher than the state-of-the-art methods.
Original languageEnglish
Article number8195347
Pages (from-to)646-659
Number of pages14
JournalTsinghua Science and Technology
Issue number6
Publication statusPublished - 1 Dec 2017


  • bagging
  • emotion cause detection
  • event extraction
  • multi-kernel SVMs

ASJC Scopus subject areas

  • General


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