论文标题
聊天活动比软件开发人员生产力的聊天情绪更好
Chat activity is a better predictor than chat sentiment on software developers productivity
论文作者
论文摘要
最近的作品提出，软件开发人员的积极情绪会对软件开发人员的生产率产生积极影响。在本文中，我们调查了两个数据来源：开发人员聊天消息（来自Slack和Hipchat）以及在200个工作日中的单个共同定位的敏捷团队的源代码提交。我们的回归分析表明，聊天消息的数量是最好的预测指标，并预测在代码的投入数量和代码线数量分别为$ r^2 $ 0.33和0.27。然后，我们添加情感分析变量，直到我们的模型不再改善，并获得0.37（提交）和0.30（代码行）的$ r^2 $值。因此，分析聊天情绪可以提高对聊天活动的生产力预测，但差异并不大。这项工作支持了以下观点：情绪状态和生产力在软件开发中链接在一起。我们发现三个积极的情绪指标，但令人惊讶的是，一个负面情绪指标与更高的生产率有关。
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.
