Tweet-Price Correlation

Analyze how crypto founder tweets correlate with token price movements. Interactive candlestick charts with tweet markers, impact statistics, and CSV export.

Data from tweet-price-charts by rohunvora.

Dashboard

Open dashboard/price-correlation.html in your browser or visit xactions.app/price-correlation.

Features

• Asset selector — switch between 15 tracked tokens ($PUMP, $HYPE, $ASTER, $LAUNCHCOIN, $JUP, $MON, $USELESS, $ZORA, $META, $WIF, $XPL, $FARTCOIN, $WLD, $ZEC, $GORK)
• TradingView candlestick chart — real OHLCV price data with 15m/1h/1D timeframes
• Tweet markers — hover for tweet text, engagement stats, 1h/24h price impact
• Data table — sortable, searchable, CSV export of all tweet events
• About view — tweet-day vs no-tweet-day comparison, impact scatter plot, summary stats

Tracked Assets

Deep Linking

Link directly to an asset with a URL hash:

price-correlation.html#pump
price-correlation.html#hype
price-correlation.html#gork

Data Format

All data lives in dashboard/data/tweet-price/. Structure:

dashboard/data/tweet-price/
├── assets.json              # Master asset list
├── pump/
│   ├── tweet_events.json    # Tweet events with price impact
│   ├── prices_1d.json       # Daily OHLCV candles
│   ├── prices_1h.json       # Hourly OHLCV candles
│   ├── prices_15m.json      # 15-minute candles (some assets)
│   └── stats.json           # Pre-computed statistics
├── hype/
│   └── ...
└── (13 more assets)

Tweet Event Schema

{
  "tweet_id": "1944804295611650538",
  "asset_id": "pump",
  "asset_name": "PUMP",
  "founder": "a1lon9",
  "timestamp": 1752512451,
  "timestamp_iso": "2025-07-14T13:00:51Z",
  "text": "the ticker is $PUMP",
  "likes": 4052,
  "retweets": 335,
  "replies": 1668,
  "impressions": 557030,
  "price_at_tweet": 0.00580901,
  "price_1h": 0.00580901,
  "price_24h": 0.00565352,
  "change_1h_pct": 0.0,
  "change_24h_pct": -2.68,
  "market_cap_at_tweet": 5808947550.65
}

Candle Schema

{
  "t": 1752523200,
  "o": 0.00556425,
  "h": 0.00597475,
  "l": 0.00537395,
  "c": 0.00552439,
  "v": 1344653.89
}

Fields: t (unix timestamp), o (open), h (high), l (low), c (close), v (volume).

Stats Schema

{
  "summary": {
    "total_tweets": 109,
    "tweets_with_price": 109,
    "date_range": { "start": "2025-07-14", "end": "2026-01-15" },
    "total_days_analyzed": 186
  },
  "daily_comparison": {
    "tweet_day_count": 72,
    "tweet_day_avg_return": 1.52,
    "tweet_day_win_rate": 54.2,
    "no_tweet_day_count": 113,
    "no_tweet_day_avg_return": -1.06,
    "no_tweet_day_win_rate": 39.8
  }
}

Browser Script

Run scripts/tweetPriceCorrelation.js in your browser DevTools console on any X/Twitter profile page. It:

1. Scrapes tweets from the current timeline
2. Fetches prices from CoinGecko or GeckoTerminal
3. Aligns each tweet to the nearest price candle
4. Computes 1h and 24h price impact
5. Exports JSON + CSV results

// Configure before running:
const CONFIG = {
  TOKEN_ID: 'solana',           // CoinGecko token ID
  NETWORK: '',                  // GeckoTerminal network (alternative)
  POOL_ADDRESS: '',             // GeckoTerminal pool (alternative)
  WINDOWS: [1, 24],             // Impact windows in hours
  MAX_TWEETS: 200,
};

Node.js Module

import { analyzeTweetPriceCorrelation } from 'xactions/analytics';

const result = await analyzeTweetPriceCorrelation({
  tweets: [{ timestamp: 1700000000000, text: 'GM' }],
  tokenId: 'solana',
  windows: [1, 24],
});

console.log(result.aligned);  // Tweets with price data attached
console.log(result.stats);    // Correlation statistics

Functions

API Endpoint

POST /api/analytics/price-correlation

Request body:

{
  "tweets": [
    { "timestamp": 1700000000000, "text": "GM" }
  ],
  "tokenId": "solana",
  "windows": [1, 24]
}

Or for DEX tokens:

{
  "tweets": [...],
  "network": "solana",
  "poolAddress": "0x...",
  "windows": [1, 24]
}

Response:

{
  "aligned": [...],
  "stats": { "totalTweets": 109, "avgChange24h": 1.52, "winRate": 54.2 },
  "meta": { "token": "solana", "priceSource": "coingecko", "pricePoints": 4444 }
}