XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection

• URL: http://arxiv.org/abs/2011.01612v2
• Date: Fri, 6 Nov 2020 10:50:06 GMT
• Title: XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection
• Authors: Emily \"Ohman, Marc P\`amies, Kaisla Kajava, J\"org Tiedemann
• Abstract summary: The dataset consists of human-annotated Finnish (25k) and English sentences (30k) 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.
• Score: 0.42056926734482064
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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