Describing Software Developers Affectiveness through Markov chain Models


In this paper, we present an analysis of more than 500K comments from open-sourcerepositories of software systems.Our aim is to empirically determine how developers interact with each otherunder certain psychological conditions generated by politeness, sentiment andemotion expressed within developers' comments.Developers involved in an open-source projects do not usually know each other; they mainly communicate through mailing lists, chat rooms, and tools such as issue tracking systems.The way in which they communicate affects the development process and the productivity of the people involved in the project.We evaluated politeness, sentiment and emotions of comments posted by developers and studied the communication flow to understand how they interacted in the presence of impolite and negative comments (and vice versa).Our analysis shows that when in presence of impolite or negative comments, the probability of the next comment being impolite or negative is 14% and 25%, respectively;  anger however,has a probability of 40% of being followed by a further anger comment.The result could help managers take control the development phases of a system, since social aspects can seriously affect a developer's productivity. In a distributed environment this may have a particular resonance.

DOI Code: 10.1285/i20705948v13n1p96

Keywords: data mining; Markov chains; human aspects in software engineering

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