# STEREO: Scientific Text Reuse in Open Access Publications

arXiv: https://arxiv.org/abs/2112.11800 · HTML: https://mlsanity.com/paper/2112.11800/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 42 references that are in the map.
- First posted on arXiv 22 Dec 2021.

## Builds on (most cited first, 6 of 6)

- [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018)
- [Mitigating Dataset Harms Requires Stewardship: Lessons from 1000 Papers](https://mlsanity.com/paper/2108.02922/) (2021)
- [Testing of Support Tools for Plagiarism Detection](https://mlsanity.com/paper/2002.04279/) (2020)
- [Patterns of Text Reuse in a Scientific Corpus](https://mlsanity.com/paper/1412.2716/) (2014)
- [Automatic Detection of Reuses and Citations in Literary Texts](https://mlsanity.com/paper/1404.2997/) (2014)
- [Wikipedia Text Reuse: Within and Without](https://mlsanity.com/paper/1812.09221/) (2018)

## Built on by (most cited first, 1 of 1)

- [Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligence](https://mlsanity.com/paper/2309.14379/) (2023)

## Abstract (arXiv)

We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains more than 91 million cases of reused text passages found in 4.2 million unique open-access publications. Featuring a high coverage of scientific disciplines and varieties of reuse, as well as comprehensive metadata to contextualize each case, our dataset addresses the most salient shortcomings of previous ones on scientific writing. Webis-STEREO-21 allows for tackling a wide range of research questions from different scientific backgrounds, facilitating both qualitative and quantitative analysis of the phenomenon as well as a first-time grounding on the base rate of text reuse in scientific publications.