PRemo: A Dataset of Emotions Found on Pull Request Discussions
Resumo
In software engineering, effective communication is key to ensuring software quality. On GitHub projects, one of the primary channels for such communication is pull request discussions. These discussions often contain high-level design decisions. Understanding communication dynamics within development teams is crucial in software engineering, and sentiments and emotions play a significant role in this context. While there are datasets available for sentiment analysis in this field, those focusing on specific emotions are rare, and some contexts, such as pull request discussions, remain underrepresented. To address these gaps, we propose a novel methodology for capturing sentiments and emotions in contextspecific data, resulting in the creation of PRemo. PRemo includes ≈1.8K manually labeled pull-request messages from 36 active opensource industry-relevant projects. It provides data on individual emotions (and their intensity), the surrounding context, and evaluator confidence. Built using a robust triple validation and two-pass labeling process, the dataset leverages an established psychological emotion model. Already applied in prior research, PRemo is a valuable resource for advancing emotion analysis in software engineering.
Palavras-chave:
repository mining, human aspects, sentiment analysis
Referências
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Mohammed R. Anany, Heba Hussien, S. Aly, and Nourhan Sakr. 2019. Influence of Emotions on Software Developer Productivity. In Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE). 75–82. DOI: 10.5220/0008068800750082
Caio Barbosa, Anderson Uchôa, Daniel Coutinho, Wesley KG Assunçao, Anderson Oliveira, Alessandro Garcia, Baldoino Fonseca, Matheus Rabelo, José Eric Coelho, Eryka Carvalho, et al. 2023. Beyond the Code: Investigating the Effects of Pull Request Conversations on Design Decay. In 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 1–12.
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Fabio Calefato, Filippo Lanubile, Federico Maiorano, and Nicole Novielli. 2018. Sentiment Polarity Detection for Software Development. In Proceedings of the 40th International Conference on Software Engineering (Gothenburg, Sweden) (ICSE ’18). Association for Computing Machinery, New York, NY, USA, 128. DOI: 10.1145/3180155.3182519
Fabio Calefato, Filippo Lanubile, Federico Maiorano, and Nicole Novielli. 2018. Sentiment polarity detection for software development. In Proceedings of the 40th International Conference on Software Engineering. 128–128.
Fabio Calefato, Filippo Lanubile, and Nicole Novielli. 2017. Emotxt: a toolkit for emotion recognition from text. In 2017 seventh international conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW). IEEE, 79–80.
Zhenpeng Chen, Yanbin Cao, Huihan Yao, Xuan Lu, Xin Peng, Hong Mei, and Xuanzhe Liu. 2021. Emoji-powered sentiment and emotion detection from software developers’ communication data. ACM Transactions on Software Engineering and Methodology (TOSEM) 30, 2 (2021), 1–48.
Daniel Coutinho, Luisa Cito, Maria Vitória Lima, Beatriz Arantes, Juliana Alves Pereira, Johny Arriel, João Godinho, Vinicius Martins, Paulo Vítor CF Libório, Leonardo Leite, et al. 2024. " Looks Good To Me;-)": Assessing Sentiment Analysis Tools for Pull Request Discussions. In Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering. 211–221.
Daniel Coutinho, Juliana Alves Pereira, Breno Braga Neves, João Correia, Caio Barbosa, Wesley K.G. Assunção, Igor Steinmacher, Marco Gerosa, Augusto Baffa, and Alessandro Garcia. 2025. opus-research/sentiment-dataset: CBSOFT 2025 Artifacts Festival - Version v2. DOI: 10.5281/zenodo.17058478
Laura Dabbish, Colleen Stuart, Jason Tsay, and Jim Herbsleb. 2012. Social coding in GitHub: transparency and collaboration in an open software repository. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work. ACM, 1277–1286.
Rafael de Mello, Roberto Oliveira, Leonardo Sousa, and Alessandro Garcia. 2017. Towards effective teams for the identification of code smells. In 2017 IEEE/ACM 10th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE). IEEE, 62–65.
Dorottya Demszky, Dana Movshovitz-Attias, Jeongwoo Ko, Alan Cowen, Gaurav Nemade, and Sujith Ravi. 2020. GoEmotions: A dataset of fine-grained emotions. arXiv preprint arXiv:2005.00547 (2020).
Paul Ekman, Tim Dalgleish, and M Power. 1999. Basic emotions. San Francisco, USA (1999).
Mateus Freira, Josemar Caetano, Johnatan Oliveira, and Humberto Marques-Neto. 2018. Analyzing the impact of feedback in GitHub on the software developer’s mood. In 2018 International Conference on Software Engineering & Knowledge Engineering.
Daniel Graziotin, Xiaofeng Wang, and Pekka Abrahamsson. 2013. Are happy developers more productive? The correlation of affective states of software developers and their self-assessed productivity. In Product-Focused Software Process Improvement: 14th International Conference, PROFES 2013, Paphos, Cyprus, June 12-14, 2013. Proceedings 14. Springer, 50–64.
Syed Fatiul Huq, Ali Zafar Sadiq, and K. Sakib. 2020. Is Developer Sentiment Related to Software Bugs: An Exploratory Study on GitHub Commits. In 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER). IEEE, 527–531. DOI: 10.1109/SANER48275.2020.9054801
Md Rakibul Islam and Minhaz F. Zibran. 2017. Leveraging Automated Sentiment Analysis in Software Engineering. In 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR). 203–214. DOI: 10.1109/MSR.2017.9
Md Rakibul Islam and Minhaz F. Zibran. 2018. DEVA: Sensing Emotions in the Valence Arousal Space in Software Engineering Text. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing (Pau, France) (SAC ’18). Association for Computing Machinery, New York, NY, USA, 1536–1543. DOI: 10.1145/3167132.3167296
Robbert Jongeling, Subhajit Datta, and Alexander Serebrenik. 2015. Choosing your weapons: On sentiment analysis tools for software engineering research. In 2015 IEEE international conference on software maintenance and evolution (ICSME). IEEE, 531–535.
Chris F Kemerer and Mark C Paulk. 2009. The impact of design and code reviews on software quality: An empirical study based on psp data. IEEE Trans. Softw. Eng. (TSE) 35, 4 (2009), 534–550.
Miikka Kuutila, M. Mäntylä, and Maëlick Claes. 2020. Chat activity is a better predictor than chat sentiment on software developers productivity. In Proceedings of the IEEE/ACM 42nd International Conference on Software EngineeringWorkshops. DOI: 10.1145/3387940.3392224
Bin Lin, Fiorella Zampetti, Gabriele Bavota, Massimiliano Di Penta, Michele Lanza, and Rocco Oliveto. 2018. Sentiment Analysis for Software Engineering: How Far Can We Go?. In Proceedings of the 40th International Conference on Software Engineering (Gothenburg, Sweden) (ICSE ’18). Association for Computing Machinery, NewYork, NY, USA, 94–104. DOI: 10.1145/3180155.3180195
Nikolaos Lykousas, Constantinos Patsakis, Andreas Kaltenbrunner, and Vicenç Gómez. 2019. Sharing emotions at scale: The vent dataset. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 13. 611–619.
Shane McIntosh, Yasutaka Kamei, Bram Adams, and Ahmed E Hassan. 2016. An empirical study of the impact of modern code review practices on software quality. Emp. Softw. Eng. (ESE) 21, 5 (2016), 2146–2189.
Alessandro Murgia, Parastou Tourani, Bram Adams, and Marco Ortu. 2014. Do Developers Feel Emotions? An Exploratory Analysis of Emotions in Software Artifacts. In Proceedings of the 11th Working Conference on Mining Software Repositories (Hyderabad, India) (MSR 2014).Association for Computing Machinery, New York, NY, USA, 262–271. DOI: 10.1145/2597073.2597086
Nicole Novielli, Fabio Calefato, Davide Dongiovanni, Daniela Girardi, and Filippo Lanubile. 2020. Can We Use SE-Specific Sentiment Analysis Tools in a Cross-Platform Setting?. In Proceedings of the 17th International Conference on Mining Software Repositories (Seoul, Republic of Korea) (MSR ’20). Association for Computing Machinery, New York, NY, USA, 158–168. DOI: 10.1145/3379597.3387446
Martin Obaidi, Lukas Nagel, Alexander Specht, and Jil Klünder. 2022. Sentiment analysis tools in software engineering: A systematic mapping study. Information and Software Technology (2022), 107018.
Marco Ortu, Alessandro Murgia, Giuseppe Destefanis, Parastou Tourani, Roberto Tonelli, Michele Marchesi, and BramAdams. 2016. The Emotional Side of Software Developers in JIRA. In Proceedings of the 13th International Conference on Mining Software Repositories (Austin, Texas) (MSR ’16). Association for Computing Machinery, New York, NY, USA, 480–483. DOI: 10.1145/2901739.2903505
Phillip Shaver, Judith Schwartz, Donald Kirson, and Cary O’connor. 1987. Emotion knowledge: further exploration of a prototype approach. Journal of personality and social psychology 52, 6 (1987), 1061.
Mauricio Soto, Zack Coker, and Claire Le Goues. 2017. Analyzing the impact of social attributes on commit integration success. In Mining Software Repositories (MSR), 2017 IEEE/ACM 14th International Conference on. IEEE, 483–486.
Patanamon Thongtanunam, Shane McIntosh, Ahmed E Hassan, and Hajimu Iida. 2015. Investigating code review practices in defective files: An empirical study of the qt system. In 12th MSR. IEEE Press, 168–179.
Jason Tsay, Laura Dabbish, and James Herbsleb. 2014. Influence of social and technical factors for evaluating contribution in GitHub. In Proceedings of the 36th international conference on Software engineering. 356–366.
Jason Tsay, Laura Dabbish, and James Herbsleb. 2014. Let’s Talk about It: Evaluating Contributions through Discussion in GitHub. In Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (Hong Kong, China) (FSE 2014). Association for Computing Machinery, New York, NY, USA, 144–154. DOI: 10.1145/2635868.2635882
Anderson Uchôa, Caio Barbosa, Daniel Coutinho, Willian Oizumi, Wesley KG Assunçao, Silvia Regina Vergilio, Juliana Alves Pereira, Anderson Oliveira, and Alessandro Garcia. 2021. Predicting design impactful changes in modern code review: A large-scale empirical study. In 2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR). IEEE, 471–482.
Anderson Uchôa, Caio Barbosa, Willian Oizumi, Publio Blenílio, Rafael Lima, Alessandro Garcia, and Carla Bezerra. 2020. How does modern code review impact software design degradation? an in-depth empirical study. In 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 511–522.
Bogdan Vasilescu, Stef Van Schuylenburg, Jules Wulms, Alexander Serebrenik, and Mark GJ van den Brand. 2014. Continuous integration in a social-coding world: Empirical evidence from GitHub. In Software Maintenance and Evolution (ICSME), 2014 IEEE International Conference on. IEEE, 401–405.
Hana Vrzakova, Andrew Begel, Laura Mehtätalo, and Roman Bednarik. 2020. Affect Recognition in Code Review: An In-situ Biometric Study of Reviewer’s Affect. J. Syst. Softw. 159 (2020). DOI: 10.1016/j.jss.2019.110434
C Wohlin, P Runeson, M Host, MC Ohlsson, B Regnell, and A Wesslen. 2000. Experimentation in software engineering: an introduction.
Yue Yu, Huaimin Wang, Vladimir Filkov, Premkumar Devanbu, and Bogdan Vasilescu. 2015. Wait for it: Determinants of pull request evaluation latency on GitHub. In Mining software repositories (MSR), 2015 IEEE/ACM 12th working conference on. IEEE, 367–371.
[n. d.]. Top Programming Languages and Their Uses - KDnuggets. [link]. (Accessed on 03/28/2024).
[n. d.]. What are different programming languages used for? - FutureLearn. [link]. (Accessed on 03/28/2024).
Toufique Ahmed, Amiangshu Bosu, Anindya Iqbal, and Shahram Rahimi. 2017. SentiCR: A customized sentiment analysis tool for code review interactions. In 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE). 106–111. DOI: 10.1109/ASE.2017.8115623
Mohammed R. Anany, Heba Hussien, S. Aly, and Nourhan Sakr. 2019. Influence of Emotions on Software Developer Productivity. In Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE). 75–82. DOI: 10.5220/0008068800750082
Caio Barbosa, Anderson Uchôa, Daniel Coutinho, Wesley KG Assunçao, Anderson Oliveira, Alessandro Garcia, Baldoino Fonseca, Matheus Rabelo, José Eric Coelho, Eryka Carvalho, et al. 2023. Beyond the Code: Investigating the Effects of Pull Request Conversations on Design Decay. In 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). IEEE, 1–12.
Caio Barbosa, Anderson Uchôa, Daniel Coutinho, Filipe Falcão, Hyago Brito, Guilherme Amaral, Vinicius Soares, Alessandro Garcia, Baldoino Fonseca, Marcio Ribeiro, et al. 2020. Revealing the social aspects of design decay: A retrospective study of pull requests. In Proceedings of the XXXIV Brazilian Symposium on Software Engineering. 364–373.
Fabio Calefato, Filippo Lanubile, Federico Maiorano, and Nicole Novielli. 2018. Sentiment Polarity Detection for Software Development. In Proceedings of the 40th International Conference on Software Engineering (Gothenburg, Sweden) (ICSE ’18). Association for Computing Machinery, New York, NY, USA, 128. DOI: 10.1145/3180155.3182519
Fabio Calefato, Filippo Lanubile, Federico Maiorano, and Nicole Novielli. 2018. Sentiment polarity detection for software development. In Proceedings of the 40th International Conference on Software Engineering. 128–128.
Fabio Calefato, Filippo Lanubile, and Nicole Novielli. 2017. Emotxt: a toolkit for emotion recognition from text. In 2017 seventh international conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW). IEEE, 79–80.
Zhenpeng Chen, Yanbin Cao, Huihan Yao, Xuan Lu, Xin Peng, Hong Mei, and Xuanzhe Liu. 2021. Emoji-powered sentiment and emotion detection from software developers’ communication data. ACM Transactions on Software Engineering and Methodology (TOSEM) 30, 2 (2021), 1–48.
Daniel Coutinho, Luisa Cito, Maria Vitória Lima, Beatriz Arantes, Juliana Alves Pereira, Johny Arriel, João Godinho, Vinicius Martins, Paulo Vítor CF Libório, Leonardo Leite, et al. 2024. " Looks Good To Me;-)": Assessing Sentiment Analysis Tools for Pull Request Discussions. In Proceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering. 211–221.
Daniel Coutinho, Juliana Alves Pereira, Breno Braga Neves, João Correia, Caio Barbosa, Wesley K.G. Assunção, Igor Steinmacher, Marco Gerosa, Augusto Baffa, and Alessandro Garcia. 2025. opus-research/sentiment-dataset: CBSOFT 2025 Artifacts Festival - Version v2. DOI: 10.5281/zenodo.17058478
Laura Dabbish, Colleen Stuart, Jason Tsay, and Jim Herbsleb. 2012. Social coding in GitHub: transparency and collaboration in an open software repository. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work. ACM, 1277–1286.
Rafael de Mello, Roberto Oliveira, Leonardo Sousa, and Alessandro Garcia. 2017. Towards effective teams for the identification of code smells. In 2017 IEEE/ACM 10th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE). IEEE, 62–65.
Dorottya Demszky, Dana Movshovitz-Attias, Jeongwoo Ko, Alan Cowen, Gaurav Nemade, and Sujith Ravi. 2020. GoEmotions: A dataset of fine-grained emotions. arXiv preprint arXiv:2005.00547 (2020).
Paul Ekman, Tim Dalgleish, and M Power. 1999. Basic emotions. San Francisco, USA (1999).
Mateus Freira, Josemar Caetano, Johnatan Oliveira, and Humberto Marques-Neto. 2018. Analyzing the impact of feedback in GitHub on the software developer’s mood. In 2018 International Conference on Software Engineering & Knowledge Engineering.
Daniel Graziotin, Xiaofeng Wang, and Pekka Abrahamsson. 2013. Are happy developers more productive? The correlation of affective states of software developers and their self-assessed productivity. In Product-Focused Software Process Improvement: 14th International Conference, PROFES 2013, Paphos, Cyprus, June 12-14, 2013. Proceedings 14. Springer, 50–64.
Syed Fatiul Huq, Ali Zafar Sadiq, and K. Sakib. 2020. Is Developer Sentiment Related to Software Bugs: An Exploratory Study on GitHub Commits. In 2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER). IEEE, 527–531. DOI: 10.1109/SANER48275.2020.9054801
Md Rakibul Islam and Minhaz F. Zibran. 2017. Leveraging Automated Sentiment Analysis in Software Engineering. In 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR). 203–214. DOI: 10.1109/MSR.2017.9
Md Rakibul Islam and Minhaz F. Zibran. 2018. DEVA: Sensing Emotions in the Valence Arousal Space in Software Engineering Text. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing (Pau, France) (SAC ’18). Association for Computing Machinery, New York, NY, USA, 1536–1543. DOI: 10.1145/3167132.3167296
Robbert Jongeling, Subhajit Datta, and Alexander Serebrenik. 2015. Choosing your weapons: On sentiment analysis tools for software engineering research. In 2015 IEEE international conference on software maintenance and evolution (ICSME). IEEE, 531–535.
Chris F Kemerer and Mark C Paulk. 2009. The impact of design and code reviews on software quality: An empirical study based on psp data. IEEE Trans. Softw. Eng. (TSE) 35, 4 (2009), 534–550.
Miikka Kuutila, M. Mäntylä, and Maëlick Claes. 2020. Chat activity is a better predictor than chat sentiment on software developers productivity. In Proceedings of the IEEE/ACM 42nd International Conference on Software EngineeringWorkshops. DOI: 10.1145/3387940.3392224
Bin Lin, Fiorella Zampetti, Gabriele Bavota, Massimiliano Di Penta, Michele Lanza, and Rocco Oliveto. 2018. Sentiment Analysis for Software Engineering: How Far Can We Go?. In Proceedings of the 40th International Conference on Software Engineering (Gothenburg, Sweden) (ICSE ’18). Association for Computing Machinery, NewYork, NY, USA, 94–104. DOI: 10.1145/3180155.3180195
Nikolaos Lykousas, Constantinos Patsakis, Andreas Kaltenbrunner, and Vicenç Gómez. 2019. Sharing emotions at scale: The vent dataset. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 13. 611–619.
Shane McIntosh, Yasutaka Kamei, Bram Adams, and Ahmed E Hassan. 2016. An empirical study of the impact of modern code review practices on software quality. Emp. Softw. Eng. (ESE) 21, 5 (2016), 2146–2189.
Alessandro Murgia, Parastou Tourani, Bram Adams, and Marco Ortu. 2014. Do Developers Feel Emotions? An Exploratory Analysis of Emotions in Software Artifacts. In Proceedings of the 11th Working Conference on Mining Software Repositories (Hyderabad, India) (MSR 2014).Association for Computing Machinery, New York, NY, USA, 262–271. DOI: 10.1145/2597073.2597086
Nicole Novielli, Fabio Calefato, Davide Dongiovanni, Daniela Girardi, and Filippo Lanubile. 2020. Can We Use SE-Specific Sentiment Analysis Tools in a Cross-Platform Setting?. In Proceedings of the 17th International Conference on Mining Software Repositories (Seoul, Republic of Korea) (MSR ’20). Association for Computing Machinery, New York, NY, USA, 158–168. DOI: 10.1145/3379597.3387446
Martin Obaidi, Lukas Nagel, Alexander Specht, and Jil Klünder. 2022. Sentiment analysis tools in software engineering: A systematic mapping study. Information and Software Technology (2022), 107018.
Marco Ortu, Alessandro Murgia, Giuseppe Destefanis, Parastou Tourani, Roberto Tonelli, Michele Marchesi, and BramAdams. 2016. The Emotional Side of Software Developers in JIRA. In Proceedings of the 13th International Conference on Mining Software Repositories (Austin, Texas) (MSR ’16). Association for Computing Machinery, New York, NY, USA, 480–483. DOI: 10.1145/2901739.2903505
Phillip Shaver, Judith Schwartz, Donald Kirson, and Cary O’connor. 1987. Emotion knowledge: further exploration of a prototype approach. Journal of personality and social psychology 52, 6 (1987), 1061.
Mauricio Soto, Zack Coker, and Claire Le Goues. 2017. Analyzing the impact of social attributes on commit integration success. In Mining Software Repositories (MSR), 2017 IEEE/ACM 14th International Conference on. IEEE, 483–486.
Patanamon Thongtanunam, Shane McIntosh, Ahmed E Hassan, and Hajimu Iida. 2015. Investigating code review practices in defective files: An empirical study of the qt system. In 12th MSR. IEEE Press, 168–179.
Jason Tsay, Laura Dabbish, and James Herbsleb. 2014. Influence of social and technical factors for evaluating contribution in GitHub. In Proceedings of the 36th international conference on Software engineering. 356–366.
Jason Tsay, Laura Dabbish, and James Herbsleb. 2014. Let’s Talk about It: Evaluating Contributions through Discussion in GitHub. In Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (Hong Kong, China) (FSE 2014). Association for Computing Machinery, New York, NY, USA, 144–154. DOI: 10.1145/2635868.2635882
Anderson Uchôa, Caio Barbosa, Daniel Coutinho, Willian Oizumi, Wesley KG Assunçao, Silvia Regina Vergilio, Juliana Alves Pereira, Anderson Oliveira, and Alessandro Garcia. 2021. Predicting design impactful changes in modern code review: A large-scale empirical study. In 2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR). IEEE, 471–482.
Anderson Uchôa, Caio Barbosa, Willian Oizumi, Publio Blenílio, Rafael Lima, Alessandro Garcia, and Carla Bezerra. 2020. How does modern code review impact software design degradation? an in-depth empirical study. In 2020 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 511–522.
Bogdan Vasilescu, Stef Van Schuylenburg, Jules Wulms, Alexander Serebrenik, and Mark GJ van den Brand. 2014. Continuous integration in a social-coding world: Empirical evidence from GitHub. In Software Maintenance and Evolution (ICSME), 2014 IEEE International Conference on. IEEE, 401–405.
Hana Vrzakova, Andrew Begel, Laura Mehtätalo, and Roman Bednarik. 2020. Affect Recognition in Code Review: An In-situ Biometric Study of Reviewer’s Affect. J. Syst. Softw. 159 (2020). DOI: 10.1016/j.jss.2019.110434
C Wohlin, P Runeson, M Host, MC Ohlsson, B Regnell, and A Wesslen. 2000. Experimentation in software engineering: an introduction.
Yue Yu, Huaimin Wang, Vladimir Filkov, Premkumar Devanbu, and Bogdan Vasilescu. 2015. Wait for it: Determinants of pull request evaluation latency on GitHub. In Mining software repositories (MSR), 2015 IEEE/ACM 12th working conference on. IEEE, 367–371.
Publicado
22/09/2025
Como Citar
COUTINHO, Daniel et al.
PRemo: A Dataset of Emotions Found on Pull Request Discussions. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SOFTWARE (SBES), 39. , 2025, Recife/PE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 326-336.
ISSN 2833-0633.
DOI: https://doi.org/10.5753/sbes.2025.9936.
