@article{nur21c,
title = {Emotion-Core: An Open Source framework for emotion detection research},
journal = {Software Impacts},
volume = {10},
pages = {100179},
year = {2021},
issn = {2665-9638},
doi = {https://doi.org/10.1016/j.simpa.2021.100179},
url = {https://www.sciencedirect.com/science/article/pii/S2665963821000774},
author = {Nurud\'in Alvarez-Gonzalez and Andreas Kaltenbrunner and Vicen\c{c} G\'omez},
keywords = {Natural language processing, Emotion detection, Multilabel classification, Research showcase},
abstract = {Identifying emotions from text is crucial for a variety of real world tasks. We describe Emotion-Core, an Open-Source 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.}
}