  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.

Software Engineering