arxiv:2011.01612

XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection

Published on Nov 3, 2020

Authors:

Jörg Tiedemann

Abstract

XED, a multilingual emotion dataset with human annotations and projected labels, is evaluated using language-specific BERT models and SVMs, showing its utility for sentiment analysis and emotion detection.

AI-generated summary

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.

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