Step 1
Mission and problem
Define why Linder exists and what fake social metrics break in creator discovery.
Linder Docs
Proof of Popularity on Abstract
A transparent social experiment to measure real preference signals, not fake views, fake likes, fake comments, or AI-generated noise.
Start swipingView presale
Writing Plan
How this documentation is structured
Step 2
Mechanics and product flow
Explain wallets, swipe actions, leaderboard logic, and privacy guarantees.
Step 3
Tokenomics and incentives
Show how LDR emissions, referrals, and weekly rewards align user + creator behavior.
Step 4
Presale and rollout
Document contribution, claim schedule, liquidity intent, and launch sequencing.
Why this social experiment exists
Social media metrics can be inflated by farms, bots, and now AI systems that simulate engagement at scale. Linder exists to measure actual preference through repeated user choice, so we can answer a hard question: who is really liked on Abstract?
What we measure
We track direct swipe decisions, not vanity metrics. Individual swipes remain private, and only aggregate popularity outcomes become visible in the leaderboard and analytics products.
Who benefits
Users earn for participating in discovery, creators gain cleaner signal quality, and the broader ecosystem gets a more trustworthy social layer than likes/comments that can be purchased or generated.
Swipe Mechanics
How the swipe system works
1. Join the arena
Connect wallet, sign in, and enter the swipe feed. Each card represents a profile in the current discovery deck.
2. Make a choice
Swipe right to like a profile. Swipe left to skip. The system records directional preference and updates aggregate rankings.
3. Earn participation rewards
Every valid right swipe currently yields 2 LDR in reward accounting, subject to launch-phase controls.
4. Leaderboard updates
Publicly visible ranking shows the strongest profiles by aggregate likes. This is the proof-of-popularity output.
Platform Flow
End-to-end platform lifecycle
Phase A
Acquisition
Users onboard and create constant preference data through swipes.
Phase B
Aggregation
Raw actions roll into popularity scores and leaderboard placements.
Phase C
Incentives
LDR rewards are distributed to keep contribution and quality discovery active.
Phase D
Monetization
Premium ranking data and ecosystem integrations fund longer-term sustainability.
Tokenomics
LDR incentive model
Right swipe reward
2 LDR
Earned for valid participation actions.
Referral reward
20 LDR
Unlocked when referral reaches 10 swipes.
Weekly top-3 pool
14,000 LDR
Top 1: 8,000, Top 2: 4,000, Top 3: 2,000.
Core design goal
Reward signal production
Token emissions are tied to user behavior that creates useful ranking data.
Presale
How the presale works
Hard cap
25 ETH
Maximum accepted contribution size.
Presale rate
125,000 LDR / ETH
Reference listing rate: 100,000 LDR / ETH.
Presale allocation
3,125,000 LDR
Total token inventory mapped to cap x presale rate.
Claim schedule
50% + 50%
Second unlock occurs 14 days after the first claim window opens.
Presale lifecycle
1) Contribute during the active presale window. 2) Sale finalizes after cap/time criteria. 3) Claim start is activated. 4) Buyers claim first 50% immediately and remaining 50% after 14 days. This pacing reduces immediate sell pressure and supports market stability during launch.