Development and Application of Sentiment Analysis Tools in Software Engineering: A Systematic Literature Review

TL;DR

This systematic literature review examines sentiment analysis tools in software engineering, highlighting their applications, methodologies, challenges, and future research directions based on 80 papers.

Contribution

It provides a comprehensive overview of sentiment analysis tools in software engineering, including data sets, approaches, and open issues, guiding future research.

Findings

Sentiment analysis is often applied to open-source projects.

Support-vector machines are commonly used for sentiment classification.

Challenges include detecting irony and sarcasm in text.

Abstract

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.