Emotion classification using massive examples extracted from the Web

Ryoko Tokuhisa, Kentaro Inui, Yuji Matsumoto

研究成果: Conference contribution

101 被引用数 (Scopus)

抄録

In this paper, we propose a data-oriented method for inferring the emotion of a speaker conversing with a dialog system from the semantic content of an utterance. We first fully automatically obtain a huge collection of emotion-provoking event instances from the Web. With Japanese chosen as a target language, about 1.3 million emotion provoking event instances are extracted using an emotion lexicon and lexical patterns. We then decompose the emotion classification task into two sub-steps: sentiment polarity classification (coarsegrained emotion classification), and emotion classification (fine-grained emotion classification). For each subtask, the collection of emotion-proviking event instances is used as labelled examples to train a classifier. The results of our experiments indicate that our method significantly outperforms the baseline method. We also find that compared with the single-step model, which applies the emotion classifier directly to inputs, our two-step model significantly reduces sentiment polarity errors, which are considered fatal errors in real dialog applications.

本文言語English
ホスト出版物のタイトルColing 2008 - 22nd International Conference on Computational Linguistics, Proceedings of the Conference
出版社Association for Computational Linguistics (ACL)
ページ881-888
ページ数8
ISBN(印刷版)9781905593446
DOI
出版ステータスPublished - 2008
外部発表はい
イベント22nd International Conference on Computational Linguistics, Coling 2008 - Manchester, United Kingdom
継続期間: 2008 8 182008 8 22

出版物シリーズ

名前Coling 2008 - 22nd International Conference on Computational Linguistics, Proceedings of the Conference
1

Other

Other22nd International Conference on Computational Linguistics, Coling 2008
国/地域United Kingdom
CityManchester
Period08/8/1808/8/22

ASJC Scopus subject areas

  • 言語および言語学
  • 計算理論と計算数学
  • 言語学および言語

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