7. Conclusions
The efficiency of a GSD team is directly tied to trust among team members. The higher is the trust, the lower is the project costs. Trust also increases communication and facilitate cooperation, coordination, knowledge and information sharing, which improve the quality of generated products.
Motivated by the importance of trust for these teams, we presented an automatic framework to estimate trust existence among members of a GSD team. It uses versioning systems, a collaborative tool used in software development, as a data source. To design the framework, we used some of the trust evidences presented in the literature that can be extracted from versioning systems data. One of the main features of the proposed framework is the use of sentiment analysis to extract some of these evidences, for example, the positive tone of the conversations.
The main contribution of this paper is in the mapping of trust evidences and elements of trust models that can be captured using sentiment analysis. We expect ARSENAL-GSD to provide a better estimative of trust existence than general automatic models in the literature since it uses sentiment analysis and a rich set of evidences. Employing sentiment analysis enables us to extract something unique for each person, thus adding subjectivity to our estimative, which is an important characteristic of trust. This subjectivity cannot be captured with the use of metrics, which are generally used in automatic models. GSD managers can benefit from ARSENAL-GSD to create teams with higher trust levels and to monitor trust level variations, so actions can be taken when the trust level decreases.
