Emotion-Core: an open source framework for emotion detection research

Identifying emotions from text is crucial for a variety of real world tasks. We describe Emotion-Core, an OpenSource framework for training, evaluating, and showcasing textual Emotion Detection models. Our framework is composed of two components: Emotion Classification and EmotionUI, which allow res...

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Detalles Bibliográficos
Autores: Alvarez-Gonzalez, Nurudin, Kaltenbrunner, Andreas, Gómez, Vicenç
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/53536
Acceso en línea:http://hdl.handle.net/10230/53536
http://doi.org/10.1016/j.simpa.2021.100179
Access Level:acceso abierto
Palabra clave:Natural language processing
Emotion detection
Multilabel classification
Research showcase
Descripción
Sumario:Identifying emotions from text is crucial for a variety of real world tasks. We describe Emotion-Core, an OpenSource framework for training, evaluating, and showcasing textual Emotion Detection models. Our framework is composed of two components: Emotion Classification and EmotionUI, which allow researchers to easily extend and reuse existing emotion detection solutions. We discuss the potential impact of our software project, including a recent publication in the findings of the International conference on Empirical Methods in Natural Language Processing (EMNLP 2021). Our code is available and free to use for interested researchers.