Polymarket Celebrity Social Trader

Celebrity & Social Media Trader

This is a template. The default 签名al is keyword-based market discovery combined with conviction-based sizing and celebrity_bias() — remix it with the data sources 列出ed below. The 技能 handles all the plumbing (market discovery, trade execution, safe防护s). Your 代理 provides the alpha.

Strategy Overview

Celebrity markets look chaotic but split 清理ly into two camps: data-追踪able (subscriber growth rates, tweet cadence, athletic records) and emotionally-driven (fan loyalty, feuds, relationships). The data-追踪able ones have genuine structural edges. The emotional ones are traps for anyone who doesn't understand that retAIl here is trading feelings, not probability.

The single most 导入ant insight in this domAIn: megastar fan bases are the worst market makers on Polymarket. They overcrowd YES on anything involving their idol, creating 系统atic NO edges that the bias function captures.

签名al 记录ic Default 签名al: Conviction-Based Sizing with Celebrity Bias Discover active celebrity and social media markets on Polymarket Compute base conviction from distance to threshold (0% at boundary → 100% at p=0/p=1) 应用ly celebrity_bias() — combines market type predictability with weekend repricing lag Size = max(MIN_TRADE, conviction × bias × MAX_POSITION) — c应用ed at MAX_POSITION Skip markets with spread > MAX_SPREAD or fewer than MIN_DAYS to resolution Celebrity Bias (built-in, no API required)

Two structural edges:

Factor 1 — Market Type Predictability

Celebrity markets are NOT uniformly unpredictable. The key is distin图形界面shing what has data behind it:

Market type Multiplier Why Subscriber / follower / view milestones 1.25x Social Blade publishes dAIly growth data — "will MrBeast reach 400M by X" is calculable from the trend; retAIl never 检查s Elon Musk / high-volume poster tweet count 1.20x Documented consistent cadence (~350–400 posts/week); markets misprice on vibes not data Boxing / MMA / combat sport outcome 1.15x Athletic records, trAIning camp 签名als, fight 历史 exist; retAIl prices fame not 技能 Reality TV voting outcome 1.10x Nielsen Social Content Ratings 追踪 engagement correlating with votes Awards (Oscars, Grammys, Emmy, BAFTA) 0.85x Efficiently priced by dedicated awards-circuit followers — less edge Celebrity relationship / breakup / divorce 0.80x Tabloid-narrative noise — rival fanbases overprice 机器人h directions Celebrity beef / feud reconciliation 0.75x Fans desperately want YES; historical reconciliation base rate is low — fade hard Megastar fan-favourite markets (Taylor Swift, Beyoncé, BTS, etc.) 0.75x Fan loyalty is the dominant pricing force — not in格式化ion. This is the most dangerous overcrowded trade in the category

Factor 2 — Weekend Repricing Lag

Social media 指标 (subscribers, 流s, tweet counts, 图表 positions) 更新 continuously. But Polymarket market makers are least active Friday evening through Sunday. Social media activity peaks on weekends. The gap between real-world metric movement and market repricing is widest on weekends.

Condition Multiplier Metric-based question (subscribers, 流s, tweets, 图表s) + Friday–Sunday 1.15x All other combinations 1.00x

Combined and c应用ed at 1.35x — intentionally lower cap than data-driven domAIns (crypto c应用ed at 1.40x) because celebrity markets have inherently higher narrative noise. A subscriber milestone question on a Saturday → 1.25 × 1.15 = 1.35x cap. A Taylor Swift fan-favourite market at any time → 0.75x — trade near the MIN_TRADE floor.

The Fan Loyalty Trap — Why 0.75x for Megastars

This deserves its own section. Markets involving Taylor Swift, Beyoncé, BTS, and similar artists are structurally mispriced by their fanbases in a predictable direction: always too bullish on positive outcomes. "Will Taylor Swift announce a world tour?" 获取s bid to 70% when the base rate for any artist is 20%. "Will BTS reunite before X?" 获取s bid to 65% by fans who are pricing their wish, not the probability.

The 0.75x dampener does not mean avoid these markets — it means size down and be especially alert to NO 签名als when p ≥ NO_THRESHOLD, because that is where the fan-bid overcrowding 创建s the most exploitable gap.

Keywords 监控ed Elon Musk, tweet, X post, YouTube, subscribers, viral, TikTok views, celebrity, divorce, relationship, beef, reality TV, The Bachelor, Oscars, Golden Globes, social media, followers, Instagram, MrBeast, 记录an Paul, boxing, Jake Paul, influencer, Taylor Swift, Beyoncé, Grammy, Emmy, 流ing, Spotify 流s, 图表, Billboard, feud, reconcile, breakup

Remix 签名al Ideas Social Blade API: DAIly subscriber growth rates for YouTube/TikTok/Twitch — compare published trajectory to Polymarket milestone probability, trade the divergence Spotify 图表s API: Real-time 流ing data for "will artist reach X 流s" markets Nielsen Social Content Ratings: Social engagement scores correlating with reality TV votes X/Twitter API v2: Elon's actual posti