[Paper Review] When the Open Source Community Meets COVID-19: Characterizing COVID-19 themed GitHub Repositories

Liu Wang, Ruiqing Li+3 more|arXiv (Cornell University)|Oct 23, 2020

Scientific Computing and Data Management31 references4 citations

TL;DR

This study presents the first large-scale analysis of 67,079 COVID-19-themed GitHub repositories collected by July 2020, using NLP-based classification to categorize them into six types and analyze contribution, development, and maintenance patterns. The key finding reveals rapid, intense early development but short-lived maintenance lifecycles, with contributors largely unaffected by lockdowns, highlighting open source's critical yet fragile role in global health emergencies.

ABSTRACT

Ever since the beginning of the outbreak of the COVID-19 pandemic, researchers from interdisciplinary domains have worked together to fight against the crisis. The open source community, plays a vital role in coping with the pandemic which is inherently a collaborative process. Plenty of COVID-19 related datasets, tools, software, deep learning models, are created and shared in research communities with great efforts. However, COVID-19 themed open source projects have not been systematically studied, and we are still unaware how the open source community helps combat COVID-19 in practice. To fill this void, in this paper, we take the first step to study COVID-19 themed repositories in GitHub, one of the most popular collaborative platforms. We have collected over 67K COVID-19 themed GitHub repositories till July 2020. We then characterize them from a number of aspects and classify them into six categories. We further investigate the contribution patterns of the contributors, and development and maintenance patterns of the repositories. This study sheds light on the promising direction of adopting open source technologies and resources to rapidly tackle the worldwide public health emergency in practice, and reveals existing challenges for improvement.

Motivation & Objective

• To systematically characterize the landscape of COVID-19-themed GitHub repositories during the early pandemic.
• To understand the contribution patterns of developers and the development lifecycle of these repositories.
• To identify challenges in long-term maintenance, data sharing, and international collaboration in open source pandemic response.

Proposed method

• Collected 67,079 GitHub repositories themed around COVID-19 using keyword-based harvesting (e.g., 'covid', 'sars', 'pandemic') up to July 2020.
• Applied natural language processing (NLP) techniques to classify repositories into six categories: data, contact tracing, toolkit, forecast & simulation, detection & diagnosis, and helpful in some ways.
• Conducted trend and popularity analysis based on repository creation dates, stars, and forks.
• Analyzed contributor activity and maintenance patterns using commit history and repository lifecycle metrics.
• Clustered repositories based on lines of code (LOC) trends over time to identify distinct development behaviors.
• Released the dataset publicly at https://covid19-repos.github.io to support future research.

Experimental results

Research questions

• RQ1 What is the popularity and temporal trend of COVID-19-themed GitHub repositories?
• RQ2 How are contributors distributed across countries, and how does lockdown impact their activity?
• RQ3 What are the dominant categories of COVID-19-themed repositories, and how do they differ in development patterns?
• RQ4 How do the development and maintenance behaviors of these repositories evolve over time?
• RQ5 What are the key challenges in long-term sustainability and international collaboration of these projects?

Key findings

• Over 67,000 COVID-19-themed repositories were created on GitHub by July 2020, with a sharp spike after WHO declared the pandemic on March 11, 2020.
• The majority of repositories were created rapidly after the pandemic declaration, indicating a swift open source community response.
• Repositories were unevenly distributed across categories, with data-related repositories being the most common, followed by contact tracing and toolkits.
• Most repositories exhibited intense early development but short-lived maintenance, with over 80% becoming inactive within a few months.
• Contributor activity remained stable or slightly increased during lockdowns, suggesting that remote collaboration on GitHub was not significantly disrupted.
• Only 5 repositories exhibited a long-term, stable codebase growth pattern, indicating that sustained development is rare in emergency-driven open source projects.