CORGI: Communal Feed Governance for Bluesky

Abstract

Recommender systems curate users’ information environments on social media platforms based on the platforms’ objectives, yet user and community input into these objectives remains limited. With the rise of federated protocols such as the AT Protocol and ActivityPub, researchers have begun investigating ways for users to meaningfully influence and design their recommendations. However, these approaches often treat recommender systems as systems designed for a single user and neglect possible community objectives. We present CORGI, an open-source AT Protocol feed generator that makes a social-feed ranking policy inspectable and governable by the community of users it jointly serves. This approach treats the recommender system as a community resource shaped by collective input. Our demo incorporates a set of 24 synthetic users to demonstrate the voting mechanism. The demonstration makes the full governance loop observable: a reviewer proposes a policy, synthetic voters respond, their ballots are aggregated, the fixed post set is reranked, and each post’s score can be inspected.