Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation

Emily Öhman, Kaisla Kajava, Jörg Tiedemann, Timo Honkela

研究成果: Conference contribution

9 被引用数 (Scopus)

抄録

This paper introduces a gamified framework for fine-grained sentiment analysis and emotion detection. We present a flexible tool, Sentimentator, that can be used for efficient annotation based on crowd sourcing and a self-perpetuating gold standard. We also present a novel dataset with multi-dimensional annotations of emotions and sentiments in movie subtitles that enables research on sentiment preservation across languages and the creation of robust multilingual emotion detection tools. The tools and datasets are public and open-source and can easily be extended and applied for various purposes.

本文言語English
ホスト出版物のタイトルWASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop
出版社Association for Computational Linguistics (ACL)
ページ24-30
ページ数7
ISBN(電子版)9781948087803
DOI
出版ステータスPublished - 2018
外部発表はい
イベント9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2018 - Brussels, Belgium
継続期間: 2018 10月 31 → …

出版物シリーズ

名前WASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop

Conference

Conference9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2018
国/地域Belgium
CityBrussels
Period18/10/31 → …

ASJC Scopus subject areas

  • 言語および言語学
  • 言語学および言語

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