Stress and Burnout in Open Source: Toward Finding, Understanding, and Mitigating Unhealthy Interactions

From AcaWiki
Jump to: navigation, search

Citation: Naveen Raman, Minxuan Cao, Yulia Tsvetkov, Christian Kästner, Bogdan Vasilescu (2020) Stress and Burnout in Open Source: Toward Finding, Understanding, and Mitigating Unhealthy Interactions.
Internet Archive Scholar (search for fulltext): Stress and Burnout in Open Source: Toward Finding, Understanding, and Mitigating Unhealthy Interactions
Wikidata (metadata): Q97040199
Download: https://cmustrudel.github.io/papers/raman20toxicity.pdf
Tagged: github (RSS)

Summary

Outline a research program for finding, understanding, and possibly mitigating unhealthy interactions in open source projects. Describe a first step, development of a Support Vector Machine (SVM) classifier to detect toxicity in GitHub issues. Analysis using classifier shows that toxicity has declined over 2012-2019, there is variation among different programming languages, and corporate projects appear to have less toxic interactions than non-corporate projects.

Theoretical and Practical Relevance

https://www.youtube.com/watch?v=7Cf7H4qrQRA presentation based on paper by one of the authors.