# On the Suitability of Hugging Face Hub for Empirical Studies

arXiv: https://arxiv.org/abs/2307.14841 · HTML: https://mlsanity.com/paper/2307.14841/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jul 2023.

## Built on by (most cited first, 8 of 8)

- [The AI Community Building the Future? A Quantitative Analysis of Development Activity on Hugging Face Hub](https://mlsanity.com/paper/2405.13058/) (2024)
- [Economies of Open Intelligence: Tracing Power & Participation in the Model Ecosystem](https://mlsanity.com/paper/2512.03073/) (2025)
- [The ATOM Report: Measuring the Open Language Model Ecosystem](https://mlsanity.com/paper/2604.07190/) (2026)
- [Cataloguing Hugging Face Models to Software Engineering Activities: Automation and Findings](https://mlsanity.com/paper/2506.03013/) (2025)
- [Securing the AI Supply Chain: What Can We Learn From Developer-Reported Security Issues and Solutions of AI Projects?](https://mlsanity.com/paper/2512.23385/) (2025)
- [Attention to Detail: Evaluating Energy, Performance, and Accuracy Trade-offs Across vLLM Configurations](https://mlsanity.com/paper/2607.09172/) (2026)
- [Responsible AI in Open Ecosystems: Reconciling Innovation with Risk Assessment and Disclosure](https://mlsanity.com/paper/2409.19104/) (2024)
- [ArtifactLinker: Linking Scientific Artifacts for Automatic State-of-the-Art Discovery](https://mlsanity.com/paper/2605.16902/) (2026)

## Abstract (arXiv)

Background. The development of empirical studies in software engineering mainly relies on the data available on code hosting platforms, being GitHub the most representative. Nevertheless, in the last years, the emergence of Machine Learning (ML) has led to the development of platforms specifically designed for developing ML-based projects, being Hugging Face Hub (HFH) the most popular one. With over 250k repositories, and growing fast, HFH is becoming a promising ecosystem of ML artifacts and therefore a potential source of data for empirical studies. However, so far there have been no studies evaluating the potential of HFH for such studies. Objective. In this proposal for a registered report, we aim at performing an exploratory study of the current state of HFH in order to investigate its suitability to be used as a source platform for empirical studies. Method. We conduct a qualitative and quantitative analysis of HFH for empirical studies. The former will be performed by comparing the features of HFH with those of other code hosting platforms, such as GitHub and GitLab. The latter will be performed by analyzing the data available in HFH.