Generate a synthetic dataset of fictional cryptocurrency scams spanning from 2015 to 2025. For each scam, include the following fields:

- Scam ID (e.g., SCAM001)
- Scam Name
- Year
- Type of Scam (e.g., Ponzi Scheme, Rug Pull, Phishing, Fake ICO, Meme Token, AI Bot Scam, etc.)
- Description (realistic but fictional scam summary)
- Amount Lost (in USD, approximate)
- Affected Users (approximate count)
- Crypto Used (e.g., BTC, ETH, BNB, USDT, MATIC, ARB, etc.)
- Scam Status (e.g., Active, Busted, Exit Scammed, Under Investigation)
- Notable Quote (a promotional tagline or slogan)
- Method of Scam (e.g., Telegram, YouTube, Discord, DMs, Influencer marketing, Twitter, Fake Website, etc.)
- Scam URL or Social Media Handle used
- Country or Region Targeted

Instructions:
- Generate 10–20 unique entries per year from 2015 through 2025.
- Reflect the major crypto trends of each year:
    - 2015–2016