# An Empirical Study On Correlation between Readme Content and Project Popularity

arXiv: https://arxiv.org/abs/2206.10772 · HTML: https://mlsanity.com/paper/2206.10772/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jun 2022.

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

- [Enhancing COBOL Code Explanations: A Multi-Agents Approach Using Large Language Models](https://mlsanity.com/paper/2507.02182/) (2025)

## Abstract (arXiv)

Readme in GitHub repositories serves as a preliminary source of information, and thus helps developers in understanding about the projects, for reuse or extension. Different types of contextual and structural content, which we refer to as categories of the content and features in the content respectively, are present in readme files, and could determine the extent of comprehension about project. Consequently, the structural and contextual aspects of the content could impact the project popularity. Studying the correlation between the content and project popularity could help in focusing on the aspects that could improve popularity, while designing the readme files. However, existing studies explore the categories of content and types of features in readme files, and do not explore their usefulness towards project popularity. Hence, we present an empirical study to understand correlation between readme file content and project popularity. We perform the study on 1950 readme files of public GitHub projects, spanning across ten programming languages, and observe that readme files in majority of the popular projects are well organised using lists and images, and comprise links to external sources. Also, repositories with readme files containing contribution guidelines and references were observed to be associated with higher popularity.