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 language | English |
|---|---|
| Pages (from-to) | 293-301 |
| Number of pages | 9 |
| Journal | CEUR Workshop Proceedings |
| Volume | 2612 |
| Publication status | Published - 2020 |
| Externally published | Yes |
| Event | 5th Conference on Digital Humanities in the Nordic Countries, DHN 2020 - Riga, Latvia Duration: 2020 Oct 21 → 2020 Oct 23 |
Keywords
- Annotator Experience
- Emotion Annotation
- Sentiment Analysis
ASJC Scopus subject areas
- Computer Science(all)