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We also have a frontend only fallback to maintain availability.\n\n\u003cimg src=\"image.png\" alt=\"drawing\" width=\"200rem\"/\u003e\n\n## Avoid Implicit Personalized Recommendation Algorithms\n\nA social media with no personalized recommendation algorithms. So no more echo chamber radicalization.\n\nThere are two ways to end personalized recommendation algorithms:\n\n1. Block user data. No user data means no user personalization.\n2. No recommendation algorithm. User data is not used for implicit (without user choice like in subscriptions) personalization.\n\nAny of the two is sufficient. My discover link does both.\n\nDiscover something new everyday. Good mood and learning ahead! \n\n## Background \n\nIt is like tiktok for web links.\n\nCompletely self reliant and you can share links with the whole world, upvote them, downvote them, and it shows these counts including visits. To prevent abuse, bad links are automatically removed if they get many downvotes that are more than 80% of total votes.\n\nThis is my contribution so you don't use personalized recommendation algorithms social media. They cause echo chamber radicalization.\n\nLet's go back to before 2005, before EdgeRank was released. \n\n## Run frontend for local testing\n```\nnpx serve . -l 44631\n```\n\n## Format code in VS Codium  \n```\nCtrl+Shift+I\n```\n\n## Add LICENSE header to new file\n```\npython addHeader.py\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabirusabil123%2Fdiscover","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabirusabil123%2Fdiscover","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabirusabil123%2Fdiscover/lists"}