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      "body": "{\"symbols\":[\"AAPL\",\"TSLA\"],\"maxMessagesPerSymbol\":20,\"includeRaw\":false}"
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    "categories": [
      "SOCIAL_MEDIA",
      "NEWS",
      "BUSINESS"
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    "title": "Stocktwits Scraper",
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    "seoTitle": "Stocktwits Scraper: Ticker Messages & Sentiment",
    "seoDescription": "Scrape Stocktwits ticker messages, sentiment, users, likes, replies, and cashtags for trading research, market monitoring, alerts, and dashboards.",
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    "notice": "NONE",
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    "isSourceCodeHidden": true,
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    "actorPermissionLevel": "LIMITED_PERMISSIONS",
    "readmeSummary": "## Stocktwits Scraper\n\nA Stocktwits-focused web scraper that collects public ticker (symbol/cashtag) conversations from Stocktwits symbol streams and produces structured, per-message records containing message text, timestamp, author metadata, engagement counts (likes, replies), bullish/bearish sentiment labels when present, referenced cashtags, a link to the original message, and an optional raw message JSON payload; it operates over HTTP against public Stocktwits symbol streams, can collect recent or paginated older messages per symbol, supports incremental collection using message identifiers, and includes runtime controls for message limits, error handling across symbols, and proxy configuration for connectivity.\n\n## Use cases\n\n- Traders tracking ticker-level discussion and market mood for watchlists and alerts  \n- Quant researchers building sentiment datasets from social finance chatter  \n- Finance journalists monitoring fast-moving narratives and breaking sentiment shifts  \n- Investor-relations teams monitoring public market chatter around events (earnings, launches, analyst reports)  \n- Automation builders creating ticker alerts for bullish or bearish spikes  \n- Analysts comparing sentiment and engagement metrics across symbols  \n- Research workflows collecting historical samples via paginated message IDs",
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