  Background: Open Source Software is the building block of modern software.
However, the prevalence of project deprecation in the open source world weakens
the integrity of the downstream systems and the broad ecosystem. Therefore it
calls for efforts in monitoring and predicting project deprecations, empowering
stakeholders to take proactive measures. Challenge: Existing techniques mainly
focus on static features on a point in time to make predictions, resulting in
limited effects. Goal: We propose a novel metric from the user-repository
network, and leverage the metric to fit project deprecation predictors and
prove its real-life implications. Method: We establish a comprehensive dataset
containing 103,354 non-fork GitHub OSS projects spanning from 2011 to 2023. We
propose repository centrality, a family of HITS weights that captures shifts in
the popularity of a repository in the repository-user star network. Further
with the metric, we utilize the advancements in gradient boosting and deep
learning to fit survival analysis models to predict project lifespan or its
survival hazard. Results: Our study reveals a correlation between the HITS
centrality metrics and the repository deprecation risk. A drop in the HITS
weights of a repository indicates a decline in its centrality and prevalence,
leading to an increase in its deprecation risk and a decrease in its expected
lifespan. Our predictive models powered by repository centrality and other
repository features achieve satisfactory accuracy on the test set, with
repository centrality being the most significant feature among all.
Implications: This research offers a novel perspective on understanding the
effect of prevalence on the deprecation of OSS repositories. Our approach to
predict repository deprecation help detect health status of project and take
actions in advance, fostering a more resilient OSS ecosystem.
