Abstract
We introduce XED, a multilingual fine-grained emotion dataset. The dataset consists of human-annotated Finnish (25k) and English sentences (30k), as well as projected annotations for 30 additional languages, providing new resources for many low-resource languages. We use Plutchik’s core emotions to annotate the dataset with the addition of neutral to create a multilabel multiclass dataset. The dataset is carefully evaluated using language-specific BERT models and SVMs to show that XED performs on par with other similar datasets and is therefore a useful tool for sentiment analysis and emotion detection.- Anthology ID:
- 2020.coling-main.575
- Volume:
- Proceedings of the 28th International Conference on Computational Linguistics
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Editors:
- Donia Scott, Nuria Bel, Chengqing Zong
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 6542–6552
- Language:
- URL:
- https://aclanthology.org/2020.coling-main.575
- DOI:
- 10.18653/v1/2020.coling-main.575
- Cite (ACL):
- Emily Öhman, Marc Pàmies, Kaisla Kajava, and Jörg Tiedemann. 2020. XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection. In Proceedings of the 28th International Conference on Computational Linguistics, pages 6542–6552, Barcelona, Spain (Online). International Committee on Computational Linguistics.
- Cite (Informal):
- XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection (Öhman et al., COLING 2020)
- PDF:
- https://preview.aclanthology.org/add_acl24_videos/2020.coling-main.575.pdf
- Code
- Helsinki-NLP/XED
- Data
- XED, GoEmotions