Emotion annotation: Rethinking emotion categorization

Research output: Contribution to journalConference articlepeer-review

Abstract

One of the biggest hurdles for the utilization of machine learning in interdisciplinary projects is the need for annotated training data which is costly to create. Emotion annotation is a notoriously difficult task, and the current annotation schemes which are based on psychological theories of human interaction are not always the most conducive for the creation of reliable emotion annotations, nor are they optimal for annotating emotions in the modality of text. This paper discusses the theory, history, and challenges of emotion annotation, and proposes improvements for emotion annotation tasks based on both theory and case studies. These improvements focus on rethinking the categorization of emotions and the overlap and disjointedness of emotion categories.

Original languageEnglish
Pages (from-to)134-144
Number of pages11
JournalCEUR Workshop Proceedings
Volume2865
Publication statusPublished - 2020
Externally publishedYes
Event5th Conference Digital Humanities in the Nordic Countries, DHN 2020 - Riga, Latvia
Duration: 2020 Oct 212020 Oct 23

Keywords

  • Emotion annotation
  • Textual expressions of emotions
  • Theories of emotion

ASJC Scopus subject areas

  • Computer Science(all)

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