Chat activity is a better predictor than chat sentiment on software developers productivity
Kuutila, Miikka; Mäntylä, Mika V.; Claes, Maëlick (2020-06-01)
Miikka Kuutila, Mika V. Mãntylã, and Maëlick Claes. 2020. Chat activity is a better predictor than chat sentiment on software developers productivity. In Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops (ICSEW'20). Association for Computing Machinery, New York, NY, USA, 553–556. DOI:https://doi.org/10.1145/3387940.3392224
© 2020 Association for Computing Machinery. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Fifth International Workshop on Emotion Awareness in Software Engineering, SEmotion 2020, https://doi.org/10.1145/3387940.3392224.
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https://urn.fi/URN:NBN:fi-fe2020100176316
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Abstract
Recent works have proposed that software developers’ positive emotion has a positive impact on software developers’ productivity. In this paper we investigate two data sources: developers chat messages (from Slack and Hipchat) and source code commits of a single co-located Agile team over 200 working days. Our regression analysis shows that the number of chat messages is the best predictor and predicts productivity measured both in the number of commits and lines of code with R2 of 0.33 and 0.27 respectively. We then add sentiment analysis variables until AIC of our model no longer improves and gets R2 values of 0.37 (commits) and 0.30 (lines of code). Thus, analyzing chat sentiment improves productivity prediction over chat activity alone but the difference is not massive. This work supports the idea that emotional state and productivity are linked in software development. We find that three positive sentiment metrics, but surprisingly also one negative sentiment metric is associated with higher productivity.
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