Social media empower distributed content creation by algorithmically harnessing "the social fabric" (explicit and implicit signals of association) to serve this content. While this overcomes the bottlenecks and biases of traditional gatekeepers, many believe it has unsustainably eroded the very social fabric it depends on by maximizing engagement for advertising revenue. This paper participates in open and ongoing considerations to translate social and political values and conventions, specifically social cohesion, into platform design. We propose an alternative platform model that includes the social fabric an explicit output as well as input. Citizens are members of communities defined by explicit affiliation or clusters of shared attitudes. Both have internal divisions, as citizens are members of intersecting communities, which are themselves internally diverse. Each is understood to value content that bridge (viz. achieve consensus across) and balance (viz. represent fairly) this internal diversity, consistent with the principles of the Hutchins Commission (1947). Content is labeled with social provenance, indicating for which community or citizen it is bridging or balancing. Subscription payments allow citizens and communities to increase the algorithmic weight on the content they value in the content serving algorithm. Advertisers may, with consent of citizen or community counterparties, target them in exchange for payment or increase in that party's algorithmic weight. Underserved and emerging communities and citizens are optimally subsidized/supported to develop into paying participants. Content creators and communities that curate content are rewarded for their contributions with algorithmic weight and/or revenue. We discuss applications to productivity (e.g. LinkedIn), political (e.g. X), and cultural (e.g. TikTok) platforms.

翻译：社交媒体通过算法化地利用"社会结构"（即显性与隐性的关联信号）来分发内容，从而赋能分布式内容创作。尽管这克服了传统信息把关人的瓶颈与偏见，但许多人认为，为最大化广告收益而优化用户参与度的模式，已不可持续地侵蚀了其所依赖的社会结构。本文参与当前开放持续的讨论，旨在将社会与政治价值及规范——特别是社会凝聚力——转化为平台设计原则。我们提出一种替代性平台模型，将社会结构同时作为显性输出与输入要素。用户是基于明确归属关系或共享态度聚类所定义社群的成员。两者皆存在内部差异，因为用户同时隶属于多个交叉社群，且社群内部本身具有多样性。根据哈钦斯委员会（1947）原则，每个社群都被理解为重视能够弥合（即实现跨群体共识）与平衡（即公平呈现）这种内部多样性的内容。内容将标注"社会溯源"标签，指明其为何种社群或用户提供弥合或平衡功能。订阅支付机制允许用户和社群通过增加算法权重，在内容推荐算法中提升其所重视内容的优先级。广告商可在获得用户或社群对应方同意后，通过支付费用或提升该方算法权重的方式实现定向投放。资源匮乏的新兴社群和用户将获得优化补贴/支持，以逐步发展为付费参与者。内容创作者与进行内容策展的社群可通过算法权重和/或收益回报其贡献。我们探讨了该模型在生产力（如LinkedIn）、政治（如X）与文化（如TikTok）类平台的应用前景。