An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets

Gias Uddin, Yann-Gaël Guéhénuc, Foutse Khomh and Chanchal K. Roy

Article (2022)

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Department:	Department of Computer Engineering and Software Engineering
PolyPublie URL:	https://publications.polymtl.ca/51116/
Journal Title:	ACM Transactions on Software Engineering and Methodology (vol. 31, no. 3)
Publisher:	ACM
DOI:	10.1145/3491211
Official URL:	https://doi.org/10.1145/3491211
Date Deposited:	18 Apr 2023 14:59
Last Modified:	08 Apr 2025 07:19

Cite in APA 7:	Uddin, G., Guéhénuc, Y.-G., Khomh, F., & Roy, C. K. (2022). An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets. ACM Transactions on Software Engineering and Methodology, 31(3), 1-38. https://doi.org/10.1145/3491211
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