COLING 2020main76 citations
XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection
Emily Öhman, Marc Pàmies, Kaisla Kajava, Jörg Tiedemann
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.
BibTeX
@inproceedings{ohman-etal-2020-xed,
title = "{XED}: A Multilingual Dataset for Sentiment Analysis and Emotion Detection",
author = {{\"O}hman, Emily and
P{\`a}mies, Marc and
Kajava, Kaisla and
Tiedemann, J{\"o}rg},
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.575/",
doi = "10.18653/v1/2020.coling-main.575",
pages = "6542--6552"
}