# Сопутствующие статьи по теме Prediction

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Prediction", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

Programmers Must Read: Job Hunting in Web3, Avoid These Four Types of High-Risk Gambling-Related Platforms

Chinese programmer "Xiao Wang" considers a Web3 career transition but faces job offers involving "perpetual contracts, on-chain gambling, and prediction markets," raising legal concerns. A legal team advises caution, identifying four high-risk platform types that may constitute illegal operations under Chinese law, despite attractive salaries and remote work: 1. **Web3 Gaming Platforms**: Often disguised as decentralized games (GameFi) but operate as on-chain casinos using USDT/ETH as chips, with smart contracts handling bets and payouts. Developers building betting logic, random number generators, or fund pools are considered key technical support in gambling operations. 2. **Perpetual Contract Development**: High-leverage crypto trading platforms (e.g., 150x) where users bet on price directions. Courts increasingly view these as gambling, and developers working on matching engines, liquidation systems, or referral programs face liability. 3. **Prediction Markets**: Framed as financial innovation for event forecasting, they essentially function as binary betting on outcomes (e.g., price movements or macro events). Technologists designing prediction contracts or oracle integrations are seen as enabling gambling mechanisms. 4. **Gambling Payment Platforms**: High-risk payment/clearing services for gambling sites, often masked as "payment solutions" or "USDT gateways." Developers building fiat/crypto deposit/withdrawal systems or currency exchange logic may be implicated in providing gambling-related financial services. Key advice: Reject any role where the core business involves "betting on outcomes with platform profit from odds/leverage." Conduct a two-step self-check: 1) Analyze the project’s overall model (white paper/website) for gambling patterns; 2) Scrutinize if your role involves critical components like betting logic, payout rules, or fund settlement. Prioritizing risk avoidance is crucial to prevent potential criminal liability and career disruption.

marsbit02/25 00:08

Programmers Must Read: Job Hunting in Web3, Avoid These Four Types of High-Risk Gambling-Related Platforms

marsbit02/25 00:08

Data Modeling: How to Improve the Quality of Interaction on Polymarket?

Polymarket, a leading prediction market platform, is anticipated to have one of the largest airdrops in the sector. This analysis provides a data-driven strategy to optimize user interactions for potential rewards. A critical finding is that public dashboards often double-count trading volume by including both sides of a trade. The true, single-sided figure is likely half of what is displayed, which will be the metric Polymarket uses internally. User distribution data reveals extreme concentration: only 0.51% of addresses profited over $1,000, and a mere 1.74% traded over $50,000. Crucially, 79% of traders have never earned even $1 in liquidity provider (LP) rewards, making LP activity a currently undervalued and highly capital-efficient interaction. Historical airdrop precedents suggest rewards will be based on active behavior—not profitability—to avoid favoring insiders. A multi-dimensional model is predicted, likely featuring: * 40% weight on trade volume (using a square root compression formula to limit whale dominance). * 35% weight on LP rewards. * 15% weight on market diversity (number of distinct markets traded in). * 10% weight on longevity (months active). The analysis advises users to accumulate genuine, on-chain provable volume across diverse markets, hold positions for 1-24 hours, and, most importantly, begin providing liquidity to accumulate LP rewards, which are a strong anti-Sybil signal. A hard cap per address is also expected to prevent excessive concentration of the airdrop.

Odaily星球日报02/22 10:57

Data Modeling: How to Improve the Quality of Interaction on Polymarket?

Odaily星球日报02/22 10:57

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