Chat activity is a better predictor than chat sentiment on software developers productivity |
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Author: | Kuutila, Miikka1; Mäntylä, Mika V.1; Claes, Maëlick1 |
Organizations: |
1University of Oulu |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.9 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2020100176316 |
Language: | English |
Published: |
Association for Computing Machinery,
2020
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Publish Date: | 2020-10-01 |
Description: |
AbstractRecent 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. see all
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ISBN Print: | 978-1-4503-7963-2 |
Pages: | 553 - 556 |
DOI: | 10.1145/3387940.3392224 |
OADOI: | https://oadoi.org/10.1145/3387940.3392224 |
Host publication: |
Fifth International Workshop on Emotion Awareness in Software Engineering, SEmotion 2020 |
Conference: |
International Workshop on Emotion Awareness in Software Engineering |
Type of Publication: |
A4 Article in conference proceedings |
Field of Science: |
113 Computer and information sciences |
Subjects: | |
Funding: |
This work has been supported by Academy of Finland grant 298020. The first author has been supported by Kaute-foundation. |
Academy of Finland Grant Number: |
298020 |
Detailed Information: |
298020 (Academy of Finland Funding decision) |
Copyright information: |
© 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. |