Textual emotion detection with complementary BERT transformers in a Condorcet’s Jury theorem assembly
Journal
Knowledge-Based Systems
ISSN
0950-7051
Publisher
Elsevier
Date Issued
2025
Author(s)
Bárcena Ruiz, Gerardo
Gil Herrera, Richard De Jesús
Type
text::journal::journal article
Abstract
This paper explores a novel approach to textual emotion detection (TED) in Spanish and English, leveraging an ensemble of partially trained BERT transformers within a Condorcet’s Jury Theorem (CJT) framework. Recognizing the challenges of limited training data and the complexities of emotion classification, this research investigates whether a combination of BERT models in the CJT ensemble can enhance performance even when individual models have incomplete training. The study evaluates different BERT modalities (BERT, RoBERTa, DistilBERT) and datasets, including SemEval-2018, XED, and Dair-ai/emotion. The main contribution is the development of a CJT ensemble, specifically the Jury Dynamic (JD), a key contribution of this research. This algorithm is designed for deployment in unsupervised production environments, eliminating the need for labeled data or continuous human supervision, leveraging Reinforcement Learning (RL). The Jury Dynamic (JD) adapts to incoming data, making it suitable for real-time applications. Experiments involve retraining BERT models with varying levels of emotional data reduction to simulate incomplete training. Results demonstrate that the CJT ensemble, particularly the JD, can effectively mitigate the negative impacts of limited training data, achieving comparable performance to fully trained models and outperforming individual models. The study highlights the importance of high-quality datasets for TED, particularly in Spanish, and proposes future research directions, including the evaluation of various classifiers and ensemble configurations. ©The authors ©Knowledge-Based Systems ©Elsevier.
License
Acceso Restringido
How to cite
Bárcena Ruiz, G., & Gil Herrera, R. D. J. (2025). Textual emotion detection with complementary BERT transformers in a Condorcet’s Jury theorem assembly. Knowledge-Based Systems, 326, 114070. https://doi.org/10.1016/j.knosys.2025.114070
Table of contents
1. Introduction -- 2. Background -- 3. Proposed conceptual model -- 4. Related Works -- 5. Experimentation -- 6. Discussion -- 7. Conclusion -- CRediT authorship contribution statement -- Declaration of competing interest -- Data availability .