  The diverse community members who contribute to the discussions on issue
tracking systems of open-source software projects often exhibit complex
affective states such as sentiments and tones. These affective states can
significantly influence the effectiveness of the issue discussions in
elaborating the initial ideas into actionable tasks that the development teams
need to address. In this paper, we present an extended empirical study to
investigate the impacts of sentiments and tones in community-generated issue
discussions. We created and validated a large dataset of sentiments and tones
in the issues posts and comments created by diverse community members in three
popular open source projects. Our analysis results drew a complex picture of
the relationships between, on the one hand, the sentiments and tones in the
issue discussions, and on the other hand, various discussion and
development-related measures such as the discussion length and the issue
resolution time. We also found that when factors such as the issue poster roles
and the issue types were controlled, sentiments and tones had varied
associations with the measures. Insights gained from these findings can support
open source community members in making and moderating effective issue
discussions and guide the design of tools to better support community
engagement.
