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A stealth Twitter/X automation bot that comments on rising tweets using multiple accounts to boost engagement and visibility at scale.

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Twitter Rising Post Comment Bot

Project Overview:

This automation bot is built to detect and comment on rising or trending tweets from high-engagement accounts—perfect for boosting brand visibility, promoting posts, or driving attention to linked content. It works by monitoring the timeline or specific profiles and commenting early with text or media to get noticed before the crowd.

It’s optimized for stealth, multi-account scale, and natural behavior emulation, making it ideal for creators, growth hackers, and marketers looking to automate Twitter engagement without getting flagged.

Core Features:

  • Undetectable Operation with Proxy Rotation: Avoids bans and rate limits using session isolation, headless browsers, and proxy cycling.
  • Real-Time Trending Tweet Detection: Identifies rising tweets based on engagement velocity, keywords, or account size.
  • Mass Commenting Support: Easily handles dozens or hundreds of accounts, with configurable delays and message variations.
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Features List:

Feature Description
Proxy Integration Automatically rotates proxies to bypass IP bans and improve account trust.
Account Session Manager Loads sessions via cookies or tokens to maintain persistent logins.
Comment Scheduler Schedules comments on rising tweets with time delays for natural behavior.
Media Attachment Support Supports adding image or video attachments with each comment.
Action Randomization Varies typing delay, scrolls, and pauses to mimic human interaction.
Keyword & Hashtag Filter Targets tweets with specific hashtags, mentions, or keywords.
Multi-Account Orchestration Handles 50–500 accounts in parallel via headless or real-device emulation.
Telegram Logging Sends logs, success/failure reports, and alerts to a Telegram bot.

Key Stats:

  • Automation Accuracy: 98%
  • Session Stability: 24/7 uptime with resume support
  • Concurrent Accounts Supported: 500+
  • Detection Avoidance Rate: Mimics humans in 99% of tests
  • Comment Success Rate: 95% across trending tweets

Technologies Used:

  • Languages: JavaScript (Node.js), Python
  • Frameworks: Puppeteer, Playwright, Selenium
  • Stealth Tools: GoLogin, Multilogin, FingerprintJS
  • Platforms: Twitter/X (web), Telegram (notifications)
  • Deployment: VPS, Docker, optional mobile farms

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