When searching for an open-source Reddit UI clone that prioritizes recommendation algorithms over UI features for a university project, it’s important to choose a project that provides a comprehensive set of backend capabilities. Several projects could satisfy these needs:
Lemmy: Lemmy is a powerful open-source Reddit alternative that offers both a user-friendly UI and sophisticated backend architecture. It’s built on the ActivityPub protocol and provides API access, which can be utilized for developing and testing recommendation algorithms. Although the UI might differ slightly from Reddit, Lemmy’s emphasis on community management features and extensibility make it a robust candidate for backend-focused projects.
Kbin: Like Lemmy, Kbin offers a federated environment with a focus on privacy and decentralization. Its architecture allows for in-depth experimentation with recommendation systems by enabling modifications to the codebase. This makes Kbin suitable for academic purposes where algorithmic innovation is prioritized over visual design.
Prismo: This is another federated link aggregator built with modern technologies. Prismo allows for exploration of community-driven content categorization, making it a solid choice for projects aimed at developing or testing recommendation engines. While Prismo is relatively new and small, it provides ample flexibility for academic experimentation.

To leverage these platforms for a recommendation algorithm-focused project, you would typically engage with the API interfaces or directly manipulate the data handling layers to implement and test your algorithms. These projects typically have active communities and documentation to aid in understanding their architectures, which is crucial for effectively integrating and experimenting with recommendation algorithms as part of your project requirements.