Chat activity is a better predictor than chat sentiment on software developers productivity
This work addresses software development teams by showing that emotional state and productivity are linked, but it is incremental as it builds on prior research with a specific dataset.
The study investigated whether chat activity or sentiment better predicts software developers' productivity, finding that the number of chat messages predicts productivity with R² values of 0.33 and 0.27 for commits and lines of code, and adding sentiment analysis slightly improves predictions to R² of 0.37 and 0.30.
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.