  Software development is a collaborative task and, hence, involves different
persons. Research has shown the relevance of social aspects in the development
team for a successful and satisfying project closure. Especially the mood of a
team has been proven to be of particular importance. Thus, project managers or
project leaders want to be aware of situations in which negative mood is
present to allow for interventions. So-called sentiment analysis tools offer a
way to determine the mood based on text-based communication. In this paper, we
present the results of a systematic literature review of sentiment analysis
tools developed for or applied in the context of software engineering. Our
results summarize insights from 80 papers with respect to (1) the application
domain, (2) the purpose, (3) the used data sets, (4) the approaches for
developing sentiment analysis tools and (5) the difficulties researchers face
when applying sentiment analysis in the context of software projects. According
to our results, sentiment analysis is frequently applied to open-source
software projects, and most tools are based on support-vector machines. Despite
the frequent use of sentiment analysis in software engineering, there are open
issues, e.g., regarding the identification of irony or sarcasm, pointing to
future research directions.
