We build, deploy, and evaluate Paper Skygest, a custom personalized social feed for scientific content posted by a user's network on Bluesky and the AT Protocol. We leverage a new capability on emerging decentralized social media platforms: the ability for anyone to build and deploy feeds for other users, to use just as they would a native platform-built feed. To our knowledge, Paper Skygest is the first and largest such continuously deployed personalized social media feed by academics, with over 50,000 weekly uses by over 1,000 daily active users, all organically acquired. First, we quantitatively and qualitatively evaluate Paper Skygest usage, showing that it has sustained usage and satisfies users; we further show adoption of Paper Skygest increases a user's interactions with posts about research, and how interaction rates change as a function of post order. Second, we share our full code and describe our system architecture, to support other academics in building and deploying such feeds sustainably. Third, we overview the potential of custom feeds such as Paper Skygest for studying algorithm designs, building for user agency, and running recommender system experiments with organic users without partnering with a centralized platform.

翻译：我们构建、部署并评估了Paper Skygest，这是一个为Bluesky及AT协议上用户网络发布的科学内容定制的个性化社交信息流。我们利用了新兴去中心化社交媒体平台的一项新能力：任何人都能为其他用户构建和部署信息流，其使用体验与平台原生构建的信息流完全一致。据我们所知，Paper Skygest是首个由学术界构建且规模最大的持续部署的个性化社交媒体信息流，每周使用量超过50,000次，每日活跃用户超过1,000名，所有用户均为自然获取。首先，我们通过定量与定性方法评估Paper Skygest的使用情况，证明其具有持续的使用量并能满足用户需求；我们进一步发现采用Paper Skygest能增加用户对科研相关帖子的互动，并揭示了互动率随帖子排序位置的变化规律。其次，我们公开全部代码并详述系统架构，以支持其他学者可持续地构建和部署此类信息流。最后，我们概述了诸如Paper Skygest这类定制信息流在研究算法设计、增强用户自主权、以及与真实用户开展推荐系统实验方面的潜力，这些实验无需与中心化平台合作即可进行。