# A Gold Standard for Emotion Annotation in Stack Overflow

arXiv: https://arxiv.org/abs/1803.02300 · HTML: https://mlsanity.com/paper/1803.02300/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Mar 2018.

## Built on by (most cited first, 4 of 4)

- [An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets](https://mlsanity.com/paper/2111.03196/) (2021)
- [Predicting Emotion Intensity in Polish Political Texts: Comparing Supervised Models and Large Language Models in a Resource-Poor Language](https://mlsanity.com/paper/2407.12141/) (2024)
- [Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?](https://mlsanity.com/paper/2110.05035/) (2021)
- [Sentiment Analysis in Software Engineering: Evaluating Generative Pre-trained Transformers](https://mlsanity.com/paper/2505.14692/) (2025)

## Abstract (arXiv)

Software developers experience and share a wide range of emotions throughout a rich ecosystem of communication channels. A recent trend that has emerged in empirical software engineering studies is leveraging sentiment analysis of developers' communication traces. We release a dataset of 4,800 questions, answers, and comments from Stack Overflow, manually annotated for emotions. Our dataset contributes to the building of a shared corpus of annotated resources to support research on emotion awareness in software development.