Affective Sentiment and Emotional Analysis of Pull Request Comments on GitHub
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Sentiment and emotional analysis on online collaborative software development forums can be very useful to gain important insights into the behaviors and personalities of the developers. Such information can later on be used to increase productivity of developers by making recommendations on how to behave best in order to get a task accomplished. However, due to the highly technical nature of the data present in online collaborative software development forums, mining sentiments and emotions becomes a very challenging task. In this work we present a new approach for mining sentiments and emotions from software development datasets using Interaction Process Analysis(IPA) labels and machine learning. We also apply distance metric learning as a preprocessing step before training a feed forward neural network and report the precision, recall, F1 and accuracy.
Cite this version of the work
Deepak Rishi (2017). Affective Sentiment and Emotional Analysis of Pull Request Comments on GitHub. UWSpace. http://hdl.handle.net/10012/12728