Describing Software Developers Affectiveness through Markov chain Models

IF 0.6 Q4 STATISTICS & PROBABILITY
Marco Ortu, C. Conversano, M. Marchesi, R. Tonelli, S. Counsell, Giuseppe Destefanis
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引用次数: 1

Abstract

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.
用马尔可夫链模型描述软件开发者的情感
在本文中,我们对来自软件系统开放源码存储库的50多万条评论进行了分析。我们的目标是通过经验来确定在某些心理条件下,开发者是如何与他人互动的,这些心理条件是由开发者评论中表达的礼貌、情绪和情绪所产生的。参与开源项目的开发人员通常彼此不认识;他们主要通过邮件列表、聊天室和诸如问题跟踪系统之类的工具进行交流。他们沟通的方式影响着开发过程和参与项目的人员的生产力。我们评估了开发者发表的评论的礼貌、情感和情绪,并研究了交流流程,以了解他们在出现不礼貌和负面评论时是如何互动的(反之亦然)。我们的分析表明,当出现不礼貌或负面评论时,下一条评论不礼貌或负面的概率分别为14%和25%;然而,愤怒有40%的可能性会引发更多的愤怒评论。结果可以帮助管理人员控制系统的开发阶段,因为社会方面会严重影响开发人员的生产力。在分布式环境中,这可能会产生特殊的共鸣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.40
自引率
14.30%
发文量
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