Publication | Closed Access
Sentiment and politeness analysis tools on developer discussions are unreliable, but so are people
33
Citations
35
References
2018
Year
Unknown Venue
Software MaintenanceEngineeringSoftware EngineeringCommunicationMultimodal Sentiment AnalysisSoftware AnalysisJournalismText MiningDeveloper DiscussionsComputational Social ScienceEmpirical Software Engineering ResearchAffective ComputingConversation AnalysisContent AnalysisWeb-based CollaborationPoliteness Analysis ToolsUser FeedbackCollaborative Software DevelopmentSocial ComputingSoftware ReviewHuman-computer InteractionPoliteness DetectionArtsOpinion Aggregation
Many software engineering researchers use sentiment and politeness analysis tools to study the emotional environment within collaborative software development. However, papers that use these tools rarely establish their reliability. In this paper, we evaluate popular existing tools for sentiment and politeness detection over a dataset of 589 manually rated GitHub comments that represent developer discussions. We also develop a coding scheme on how to quantify politeness for conversational texts found on collaborative platforms. We find that not only do the tools have a low agreement with human ratings on sentiment and politeness, human raters also have a low agreement among themselves.
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