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...
| Autores: | , , |
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| 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 |
| 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. |
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