Software development is a collaborative activity in which developers interact to create and maintain a complex software system. Human collaboration inevitably evokes emotions like joy or sadness, which can affect the collaboration either positively or negatively, yet not much is known about the individual emotions and their role for software development stakeholders. In this study, we analyze whether development artifacts like issue reports carry any emotional information about software development. This is a first step towards verifying the feasibility of an automatic tool for emotion mining in software development artifacts: if humans cannot determine any emotion from a software artifact, neither can a tool. Analysis of the Apache Software Foundation issue tracking system shows that developers do express emotions (in particular gratitude, joy and sadness). However, the more context is provided about an issue report, the more human raters start to doubt and nuance their interpretation of emotions. More investigation is needed before building a fully automatic emotion mining tool.
Do developers feel emotions? an exploratory analysis of emotions in software artifacts
ORTU, MARCO
2013-01-01
Abstract
Software development is a collaborative activity in which developers interact to create and maintain a complex software system. Human collaboration inevitably evokes emotions like joy or sadness, which can affect the collaboration either positively or negatively, yet not much is known about the individual emotions and their role for software development stakeholders. In this study, we analyze whether development artifacts like issue reports carry any emotional information about software development. This is a first step towards verifying the feasibility of an automatic tool for emotion mining in software development artifacts: if humans cannot determine any emotion from a software artifact, neither can a tool. Analysis of the Apache Software Foundation issue tracking system shows that developers do express emotions (in particular gratitude, joy and sadness). However, the more context is provided about an issue report, the more human raters start to doubt and nuance their interpretation of emotions. More investigation is needed before building a fully automatic emotion mining tool.
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