FairTrace is a decentralized platform that puts users in control of content algorithms. It allows individuals to customize their feed preferences (likes, comments, recency), view transparent scoring.
In a world ruled by invisible algorithms, FairTrace flips the script — giving power back to the people. Imagine a social feed where you control what rises to the top: deep conversations, fresh takes, or pure popularity. Every post reveals its score, every formula is open source, and every change is up for a vote. No black boxes. No hidden agendas.
Powered by community governance and AI-assisted insight from Gemini, FairTrace lets users co-create the algorithms they live by — one transparent tweak at a time.
This isn’t just a platform.
It’s algorithmic democracy.
🛠️ FairTrace – Hackathon Development Process 🧠 1. Ideation & Problem Mapping We began by identifying four core challenges in today’s digital ecosystems: • Lack of algorithm transparency • No user control over content curation • Absence of collective governance • No fair path to economic participation Inspired by these problems, we envisioned FairTrace — a transparent, community-governed content algorithm platform. ⸻ 🧩 2. Feature Planning We brainstormed and prioritized features that directly address the fairness criteria: • 🔍 Transparent scoring breakdown on every post • 🎛️ Customizable feed preferences (Likes, Comments, Recency) • 🗳️ Community proposal + voting system • 🤖 AI-powered scoring suggestions using Gemini API • 📈 Real-time impact visualization of algorithm changes ⸻ 🧑💻 3. Tech Stack & Setup • Frontend: Next.js with Tailwind CSS • Backend: Firebase Functions (Node.js) • Database: Firestore for real-time updates • AI: Gemini API integration for smart formula suggestions • Auth & Hosting: Firebase We structured the repo for modularity and clear version control of each algorithm proposal. ⸻ ⚙️ 4. Implementation Highlights • Built a live feed simulator where posts update based on user-selected weight sliders. • Implemented a score calculator with real-time results and visual breakdown. • Created a proposal submission flow with vote-up/down and auto-versioning. • Integrated Gemini AI suggestions to recommend better scoring formulas based on post trends and fairness metrics. • Visualized before/after impact with interactive graphs to show transparency in action. ⸻ 🧪 5. Testing & Refinement • Ran mock feeds with varying slider configs to verify impact • Tested voting logic and edge cases (e.g., controversial posts, comment-heavy vs like-heavy) • Validated AI-generated formulas and auto-applied them to content ranking ⸻ 🚀 6. Final Touches • Designed a clean, intuitive UI with community-first aesthetics • Wrote clear documentation, a transparent README, and a pitch script • Packaged the platform for Firebase hosting with a working demo and deployable code ⸻ ✨ Outcome We built not just a prototype, but a proof-of-concept for algorithmic democracy — where users control the feed, propose the rules, and shape the future of digital visibility.
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