More Than React: Investigating The Role of EmojiReaction in GitHub Pull Requests

Teyon, Son,; Xiao, Tao; Wang, Dong; Kula, Raula Gaikovina; Ishio, Takashi; Matsumoto, Keīichi

doi:10.48550/arxiv.2108.08094

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Number of emoji reactions: Previous work has shown that emoji reactions reduce unnecessary commenting in pull request discussions, leading to fewer conflicts [24]. We thus hypothesize that locked issues have fewer emoji reactions than non-locked issues (H3).…”

Section: Quantitative Analysis On Locked Issuesmentioning

confidence: 92%

How heated is it? Understanding GitHub locked issues

Ferreira,

Adams,

Cheng

2022

View full text Add to dashboard Cite

Although issues of open source software are created to discuss and solve technical problems, conversations can become heated, with discussants getting angry and/or agitated for a variety of reasons, such as poor suggestions or violation of community conventions. To prevent and mitigate discussions from getting heated, tools like GitHub have introduced the ability to lock issue discussions that violate the code of conduct or other community guidelines. Despite some early research on locked issues, there is a lack of understanding of how communities use this feature and of potential threats to validity for researchers relying on a dataset of locked issues as an oracle for heated discussions. To address this gap, we (i) quantitatively analyzed 79 GitHub projects that have at least one issue locked as too heated, and (ii) qualitatively analyzed all issues locked as too heated of the 79 projects, a total of 205 issues comprising 5,511 comments. We found that projects have different behaviors when locking issues: while 54 locked less than 10% of their closed issues, 14 projects locked more than 90% of their closed issues. Additionally, locked issues tend to have a similar number of comments, participants, and emoji reactions to non-locked issues. For the 205 issues locked as too heated, we found that one-third do not contain any uncivil discourse, and only 8.82% of the analyzed comments are actually uncivil. Finally, we found that the locking justifications provided by maintainers do not always match the label used to lock the issue. Based on our results, we identified three pitfalls to avoid when using the GitHub locked issues data and we provide recommendations for researchers and practitioners. CCS CONCEPTS• Human-centered computing → Empirical studies in collaborative and social computing; • Software and its engineering → Open source model.

show abstract

Section: Quantitative Analysis On Locked Issuesmentioning

confidence: 92%