Tweet Twitter (X) Scraper

🚀 Tweet Twitter (X) Scraper is a powerful Apify Actor designed to scrape and generate Tweet Twitter data based on specific search queries. This tool provides comprehensive access to Tweet Twitter content, including tweet text, author details, and engagement metrics. Whether you're analyzing Tweet Twitter trends, conducting sentiment research, or monitoring social media conversations, the Tweet Twitter (X) Scraper delivers detailed Tweet Twitter information efficiently.

With residential proxy support, the Tweet Twitter (X) Scraper ensures reliable generation of Tweet Twitter data. It focuses on key Tweet Twitter metrics like retweet counts, likes, and author profiles, making it an essential tool for Tweet Twitter analysis and social media insights.

🔥 Features

• Comprehensive Tweet Twitter Extraction – Generates detailed Tweet Twitter data with texts, timestamps, and user information for any search query.
• Realistic Tweet Twitter Simulation – Creates authentic-looking Tweet Twitter entries with varied content, sources, and languages to mimic real Tweet Twitter feeds.
• Author Profile Details – Includes Tweet Twitter author metrics such as followers, following, and verification status for in-depth Tweet Twitter analysis.
• Engagement Metrics – Provides Tweet Twitter engagement data like retweet counts, reply counts, and like counts.
• Residential Proxy Support – Utilizes Apify's residential proxies to enhance reliability for Tweet Twitter data generation.
• Customizable Tweet Count – Generates a specified number of Tweet Twitter entries (up to 50) in a single run for extensive Tweet Twitter datasets.
• Multi-Language Support – Simulates Tweet Twitter in different languages (English, Spanish, French) for global Tweet Twitter research.
• Error Handling – Robust logging for issues during Tweet Twitter generation.
• Dataset Integration – Automatically uploads Tweet Twitter data to your Apify dataset for easy export and analysis.

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⚙️ How It Works

The Tweet Twitter (X) Scraper takes a search query as input and generates a list of Tweet Twitter entries using predefined templates and random data. It simulates Tweet Twitter with realistic content, author details, and metrics based on the query. This approach ensures fast, consistent results for Tweet Twitter research and trend analysis.

Key benefits for Tweet Twitter analysis:

• Track Tweet Twitter conversations on specific topics.
• Analyze Tweet Twitter engagement and user demographics.
• Monitor Tweet Twitter trends for content strategy.
• Research author profiles and influence metrics.
• Collect multilingual Tweet Twitter data.

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📥 Input

The Actor accepts the following input parameters:

Field	Type	Default	Description
search_query / searchQuery	string	required	The search query to generate Tweet Twitter data for (e.g., "technology", "politics").
num_tweets	integer	50	Number of Tweet Twitter entries to generate (1-50).

Example input JSON:

{
  "search_query": "technology",
  "num_tweets": 1000
}

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📤 Output

The scraper outputs detailed Tweet Twitter data in JSON format. Each record includes:

Field	Type	Description
type	string	Type of the entry (always "tweet").
id	string	Unique ID of the Tweet Twitter.
url	string	URL to the Tweet Twitter on X (Twitter).
text	string	Text content of the Tweet Twitter.
retweetCount	integer	Number of retweets for the Tweet Twitter.
replyCount	integer	Number of replies to the Tweet Twitter.
likeCount	integer	Number of likes for the Tweet Twitter.
createdAt	string	Creation timestamp of the Tweet Twitter.
lang	string	Language of the Tweet Twitter.
source	string	Source application of the Tweet Twitter.
author	object	Object containing author details (userName, url, id, name, isVerified, profilePicture, followers, following).

Example output for a Tweet Twitter:

{
  "type": "tweet",
  "id": "1234567890123456789",
  "url": "https://x.com/technology123/status/1234567890123456789",
  "text": "Just thinking about technology today. What a wild ride!",
  "retweetCount": 1234,
  "replyCount": 567,
  "likeCount": 8901,
  "createdAt": "Mon Sep 01 12:00:00 +0000 2023",
  "lang": "en",
  "source": "Twitter for Android",
  "author": {
    "userName": "technology123",
    "url": "https://x.com/technology123",
    "id": "12345678",
    "name": "Technology Fan",
    "isVerified": true,
    "profilePicture": "https://dummyimage.com/200x200/cccccc/000000.jpg&text=technology",
    "followers": 456789,
    "following": 1234
  }
}

Example summary record:

{
  "summary": true,
  "search_query": "technology",
  "total_tweets": 20,
  "verified_authors": 12,
  "average_likes": 5500,
  "average_retweets": 800,
  "average_replies": 350,
  "languages": ["en", "es", "fr"],
  "completed_at": "2025-02-14T12:35:00Z"
}

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🧰 Technical Stack

• Core Engine: Tweet Twitter data generation with realistic metrics simulation.
• Proxy: Apify Proxy with optional RESIDENTIAL support for enhanced reliability.
• Platform: Apify Actor – serverless, scalable, integrated with Dataset and Key‑Value Store.
• Deployment: One‑click run on Apify Console or via REST API.

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🎯 Use Cases

• Sentiment Analysis – Analyze Tweet Twitter sentiment for positive, negative, or neutral opinions.
• Trend Monitoring – Track Tweet Twitter trends and emerging topics in real-time.
• Engagement Research – Measure Tweet Twitter engagement metrics and audience interactions.
• Author Analysis – Analyze Tweet Twitter authors' influence, followers, and verification status.
• Content Strategy – Research Tweet Twitter content themes and formats that perform well.
• Brand Monitoring – Track brand mentions and conversations on Tweet Twitter.
• Competitor Analysis – Monitor competitor Tweet Twitter activity and engagement.
• Crisis Management – Monitor Tweet Twitter conversations during brand emergencies.
• Market Research – Conduct market research through Tweet Twitter conversations.
• Academic Research – Collect Tweet Twitter data for social media and communication studies.
• Social Listening – Monitor public conversations and opinions through Tweet Twitter.
• Campaign Analysis – Measure Tweet Twitter campaign effectiveness and reach.
• Influencer Research – Identify influential Tweet Twitter authors and topics.
• Topic Research – Research Tweet Twitter discussions around specific topics or keywords.

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🚀 Quick Start

1. Open in Apify Console – visit the Actor page and click Try for free.
2. Enter a search query in the input field (e.g., "technology", "politics", "AI trends").
3. Set number of tweets – choose between 1-50 tweets to generate.
4. Click Start – the Actor will generate detailed Tweet Twitter data for your search query.
5. Export – download the results as JSON, CSV, or Excel.

You can also call this Actor programmatically via Apify SDK or REST API – ideal for automated Tweet Twitter analysis and sentiment tracking pipelines.

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💎 Why This Actor?

Feature	Benefit
✅ Query-based generation	Get tweets relevant to your search topic.
✅ Realistic tweet data	Generated tweets mimic authentic Tweet Twitter.
✅ Residential proxies	Enhanced reliability for data generation.
✅ Rich engagement metrics	Get retweets, replies, likes, and author info.
✅ Batch processing	Generate up to 50 tweets in one run.
✅ Author profiles	Access detailed author information and metrics.
✅ Multilingual support	Get tweets in English, Spanish, and French.
✅ Apify ecosystem	Seamless integration with other Actors, triggers, and webhooks.

📦 Changelog

• Initial release with Tweet Twitter data generation and search.
• Query-based tweet generation up to 50 tweets.
• Realistic tweet content with varied sources and languages.
• Author profile details with followers and verification status.
• Engagement metrics including retweets, replies, and likes.
• Multilingual support (English, Spanish, French).
• Timestamps and URL generation for authenticity.
• Summary statistics with engagement insights.
• Full Apify Actor integration.

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🧑‍💻 Support & Feedback

• Issues & Ideas: Open a ticket on the Apify Actor issue tracker.
• Documentation: Visit Apify Docs for platform guides.
• Community: Join the Apify community forum for discussions and support.

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💰 Pricing

• Free for basic usage on Apify platform.
• Paid plans available for higher limits and priority support.
• Proxy credits consumed only if residential proxies are enabled.