Challenges in annotation: Annotator experiences from a crowdsourced emotion annotation task

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3 Citations (Scopus)

Abstract

With the prevalence of machine learning in natural language processing and other fields, an increasing number of crowd-sourced data sets are created and published. However, very little has been written about the annotation process from the point of view of the annotators. This pilot study aims to help fill the gap and provide insights into how to maximize the quality of the annotation output of crowd-sourced annotations with a focus on fine-grained sentence-level sentiment and emotion annotation from the annotators point of view.

Original languageEnglish
Pages (from-to)293-301
Number of pages9
JournalCEUR Workshop Proceedings
Volume2612
Publication statusPublished - 2020
Externally publishedYes
Event5th Conference on Digital Humanities in the Nordic Countries, DHN 2020 - Riga, Latvia
Duration: 2020 Oct 212020 Oct 23

Keywords

  • Annotator Experience
  • Emotion Annotation
  • Sentiment Analysis

ASJC Scopus subject areas

  • Computer Science(all)

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