Analysing Developers Affectiveness through Markov chain Models

TL;DR

This study analyzes over 500,000 developer comments from open-source projects to understand how politeness, sentiment, and emotion influence communication flow and developer productivity, using Markov chain models.

Contribution

It introduces a novel application of Markov chain models to analyze psychological and emotional dynamics in developer communication.

Findings

Negative comments increase the likelihood of subsequent negative comments by 14%.

Anger has a 40% chance of being followed by more anger.

Impoliteness and negativity significantly influence communication patterns.

Abstract

In this paper, we present an analysis of more than 500K comments from open-source repositories of software systems. Our aim is to empirically determine how developers interact with each other under certain psychological conditions generated by politeness, sentiment and emotion expressed in developers' comments. Developers involved in 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.