Abstract
Reproducibility is an important feature of science; experiments are retested, and analyses are repeated. Trust in the findings increases when consistent results are achieved. Despite the importance of reproducibility, significant work is often involved in these efforts, and some published findings may not be reproducible due to oversights or errors. In this paper, we examine a myriad of features in scholarly articles published in computer science conferences and journals and test how they correlate with reproducibility. We collected data from three different sources that labeled publications as either reproducible or irreproducible and employed statistical significance tests to identify features of those publications that hold clues about reproducibility. We found the readability of the scholarly article and accessibility of the software artifacts through hyperlinks to be strong signals noticeable amongst reproducible scholarly articles.- Anthology ID:
- 2022.wiesp-1.16
- Volume:
- Proceedings of the first Workshop on Information Extraction from Scientific Publications
- Month:
- November
- Year:
- 2022
- Address:
- Online
- Venue:
- WIESP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 140–144
- Language:
- URL:
- https://aclanthology.org/2022.wiesp-1.16
- DOI:
- Cite (ACL):
- Akhil Pandey Akella, Hamed Alhoori, and David Koop. 2022. Reproducibility Signals in Science: A preliminary analysis. In Proceedings of the first Workshop on Information Extraction from Scientific Publications, pages 140–144, Online. Association for Computational Linguistics.
- Cite (Informal):
- Reproducibility Signals in Science: A preliminary analysis (Akella et al., WIESP 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.wiesp-1.16.pdf