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 humanannotated 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.
Topics & Concepts
Computer scienceSentiment analysisArtificial intelligenceEmotion detectionNatural language processingSupport vector machineCore (optical fiber)Emotion recognitionMachine learningTelecommunicationsSentiment Analysis and Opinion MiningTopic ModelingHate Speech and Cyberbullying Detection