Chat activity is a better predictor than chat sentiment on software developers productivity

April 21, 2020 Β· Declared Dead Β· πŸ› International Conference on Software Engineering

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Authors Miikka Kuutila, Mika MΓ€ntylΓ€, MaΓ«lick Claes arXiv ID 2004.09786 Category cs.SE: Software Engineering Citations 17 Venue International Conference on Software Engineering Last Checked 3 months ago
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 $R^2$ of 0.33 and 0.27 respectively. We then add sentiment analysis variables until AIC of our model no longer improves and gets $R^2$ 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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