Abstract
Open source software development has become more social and collaborative, evident GitHub. Since 2016, GitHub started to support more informal methods such as emoji reactions, with the goal to reduce commenting noise when reviewing any code changes to a repository. From a code review context, the extent to which emoji reactions facilitate a more efficient review process is unknown. We conduct an empirical study to mine 1,850 active repositories across seven popular languages to analyze 365,811 Pull Requests (PRs) for their emoji reactions against the review time, first-time contributors, comment intentions, and the consistency of the sentiments. Answering these four research perspectives, we first find that the number of emoji reactions has a significant correlation with the review time. Second, our results show that a PR submitted by a first-time contributor is less likely to receive emoji reactions. Third, the results reveal that the comments with an intention of information giving, are more likely to receive an emoji reaction. Fourth, we observe that only a small proportion of sentiments are not consistent between comments and emoji reactions, i.e., with 11.8% of instances being identified. In these cases, the prevalent reason is when reviewers cheer up authors that admit to a mistake, i.e., acknowledge a mistake. Apart from reducing commenting noise, our work suggests that emoji reactions play a positive role in facilitating collaborative communication during the review process.
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Data Availability
The datasets generated during and/or analysed during the current study are available in the GitHub repository, https://github.com/NAIST-SE/EmojiReaction_PR.
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Acknowledgements
This work is supported by Japanese Society for the Promotion of Science (JSPS) KAKENHI Grant Numbers 18H04094 and 20K19774 and 20H05706.
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The authors declare that Raula Gaikovina Kula and Yasutaka Kamei are members of the EMSE Editorial Board. All co-authors have seen and agree with the contents of the manuscript and there is no financial interest to report.
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Wang, D., Xiao, T., Son, T. et al. More than React: Investigating the Role of Emoji Reaction in GitHub Pull Requests. Empir Software Eng 28, 123 (2023). https://doi.org/10.1007/s10664-023-10336-5
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DOI: https://doi.org/10.1007/s10664-023-10336-5