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      "body": "{ \"helloWorld\": 123 }",
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      "SOCIAL_MEDIA"
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    "title": "Tweet(X)/Twitter scraper|$0.05/1K| Pay-Per Result v2",
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    "isCritical": false,
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    "isSourceCodeHidden": true,
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    "actorPermissionLevel": "LIMITED_PERMISSIONS",
    "readmeSummary": "## Tweet(X) Fast & Cheapest scraper\n\nA Twitter (X) scraping Actor for fast, high-volume extraction of tweets, user profiles, and engagement metrics using a pay-per-result pricing model. Implements real-time and batch tweet collection with support for time-range limits, complex search queries, conversation/thread extraction, sorting and filtering by engagement thresholds and media type, and filters for verified or subscription-status accounts. Produces structured JSON-style records containing tweet text, timestamps, language, client/source, engagement counts (likes, replies, retweets, quotes, view counts), conversation and reply relationships, quoted/retweeted references, embedded media metadata, URLs, and comprehensive author profile metadata (display name, username, bio, follower/following counts, profile and banner images, creation date, verification/Blue status). Designed for automated, high-throughput scraping and monitoring workflows including real-time influencer and activity tracking.\n\n## Use cases\n\n- Collecting tweets matching complex search queries and time ranges for analysis or archiving\n- Extracting user profile metadata and follower/following counts for research or monitoring\n- Monitoring keyword trends and competitor activity on Twitter (X)\n- Real-time tracking of influencers and second-level tweet activity (thread/reply monitoring)\n- Monitoring username changes and follow/unfollow activity in real time\n- Filtering and collecting tweets by engagement thresholds (minimum likes, replies, retweets) and by media type (images, video, quotes, replies)\n- Extracting conversation and thread data for conversational analysis and reply-path reconstruction",
    "deploymentKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDW3X5bjT7cuQ5TOpfAXiI7Ls1uwLmjWRsXVkBeJblMrxQDnvRD9UeYbSUi1R2ABDzlUPQ1eLHOGx5x1hvJzHQAI3NPPsYdGcTwyDEDr5N+nI5lHE4ppqc9KK3YBxPKWrbMDX8AJ8qSm6AeHFTndKPZnX0nmLQMGebWloNbdwe1Qv5UuNJX+me6g6yZ7Ky0laGnbf4O42uJtXkf/Ax2dFI2Od0fX9GFU3z1rSRAI4xBBzBB9FBIHNdT3iLDkZv2UghV3k7+2Tk6I/9KClNMOQQeZiqepRTnKuP8FyGE0pfEAyNmx99fBrns1+hQ9wbPz0MKhR348WoGk5VJAGKd3RAL \n"
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}