Emotion cause extraction, a challenging task with corpus construction

Lin Gui, Ruifeng Xu, Qin Lu, Dongyin Wu, Yu Zhou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

18 Citations (Scopus)


2016. In this paper, we present a new challenging task for emotion analysis called emotion cause extraction. In this task, we do not need to identify the emotion category or emotion component of text. We focus on the emotion cause, a.k.a the reason or stimulant of an emotion. Since there is no open dataset available, the lack of annotated resources has limited the research in this area. Thus, we first built an annotated dataset for this task using SINA city news which follows the scheme of W3C Emotion Markup Language. We then present an emotion cause detection method using event extraction where a one-hot representation method is using to represent events in text. Because traditional event representation method does not consider the emotion category caused by the event, we modified the definition of event with a more reasonable improvement. Even with a limited training set, we can still extract sufficient features for analysis. Evaluations show that our approach achieves 7.68% higher F-measure than other reported methods. The contributions of our work include both resources and algorithm development.
Original languageEnglish
Title of host publicationSocial Media Processing - 5th National Conference, SMP 2016, Proceedings
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9789811029929
Publication statusPublished - 1 Jan 2016
Event5th National Conference on Social Media Processing, SMP 2016 - Nanchang, China
Duration: 29 Oct 201630 Oct 2016

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929


Conference5th National Conference on Social Media Processing, SMP 2016

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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