An empirical study of emoji use in software development communication

Rong, Shiyue; Wang, Weisheng; Mannan, Umme Ayda; Almeida, Eduardo Santana de; Zhou, Shurui; Ahmed, Iftekhar

doi:10.1016/j.infsof.2022.106912

Cited by 8 publications

(1 citation statement)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Chen et al (2021) learned representations of SE-related texts through emoji prediction by leveraging Tweets and GitHub posts containing emojis. Rong et al (2022) discovered the usage of emojis in software development. Their results showed that emojis tend to be used during every phase of a conversation on GitHub regardless of the developers' roles.…”

Section: Modern Communication In Software Developmentmentioning

confidence: 99%

More than React: Investigating The Role of Emoji Reaction in GitHub Pull Requests

Teyon¹,

Xiao²,

Wang³

et al. 2021

Preprint

View full text Add to dashboard Cite

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.

show abstract

Section: Modern Communication In Software Developmentmentioning

confidence: 99%