Datasets:
Dataset Viewer
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bitcoin: {
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query_metadata: {
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uuid: "6fbcd8e7-1d0a-493d-8b00-358242cac133",
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submitted_at: "2025-08-12T11:56:25.172904",
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fetched_at: "2025-08-12T12:14:54.140846",
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max_results: 100
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},
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search_result: [
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{
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id: "1955297325670182932",
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content: "@Bitcoin 1LSPwV2qy5TAk33wue4N8P9eEyyM1Z4c4A",
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metadata: {
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author: "",
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conversation_id: "1955296681442075037",
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lang: "",
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tweet_id: 1955297325670183000,
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user_id: "1894471301940875265",
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username: "MarcoDelgado212"
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},
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created_at: "0001-01-01T00:00:00Z"
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},
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{
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id: "1955297322838991184",
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content: "@Bitcoin Omo see money",
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metadata: {
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author: "",
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conversation_id: "1955296681442075037",
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tweet_id: 1955297322838991000,
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user_id: "1200613772605476867",
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username: "OGBONNAGIDEONUC"
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},
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created_at: "0001-01-01T00:00:00Z"
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},
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{
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id: "1955297318934118624",
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content: "@rajatsonifnance LTV collateral is usually insane, and you're taking significant counterparty risk by letting someone else hold your bitcoin.\n\nI'm sure this is reasonable arrangement for some, but it didn't pencil out for me. Considered it instead of a mortgage when I couldn't find financing.",
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metadata: {
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author: "",
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conversation_id: "1955078243855503447",
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created_at: "2025-08-12T15:56:23Z",
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lang: "",
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tweet_id: 1955297318934118700,
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user_id: "11071132",
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username: "RaleighC"
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},
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created_at: "0001-01-01T00:00:00Z"
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},
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{
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id: "1955297318376190308",
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content: "@Bitcoin What's that?",
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metadata: {
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author: "",
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conversation_id: "1955296681442075037",
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created_at: "2025-08-12T15:56:23Z",
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End of preview. Expand
in Data Studio
🐦 X-Twitter Scraper: Real-Time Search and Data Extraction Tool
Search and scrape X-Twitter (formerly Twitter) for posts by keyword, account, or trending topics.
This no-code tool makes it easy to generate real-time, LLM-ready datasets for any AI or content use case.
Get started with real-time scraping and instantly structure tweet data into clean JSON.
🚀 Key Features
- ⚡ Real-Time Fetch – Stream the latest tweets the moment they’re posted
- 🎯 Flexible Search – Filter by keywords, hashtags, cashtags, accounts, or trending topics
- 📈 Engagement Metrics – Pull tweet content with likes, replies, reposts & timestamps
- 🧩 LLM-Ready Output – Output in clean JSON for agents, RAG, fine-tuning, or analytics
- 💸 Free Tier – Up to 100 searches during beta; toggle up to 25 tweets per query
🛠 How It Works
- Open the Scraper Tool
- Enter your query – keyword,
#hashtag,@user, or$cashtag - Choose tweet count – up to 25 tweets per search
- Run the search – engine fetches fresh tweets in real time
- Export the results – copy or download JSON for use in any pipeline
🔥 Popular Use Cases
- Sentiment and price prediction for crypto or stocks
- Trend discovery & viral content tracking
- News & political monitoring in real time
- Creating LLM training datasets
- Feeding live data to AI agents
- …and more!
📂 Dataset Format
Each tweet is structured in LLM-friendly JSON with fields like:
{
"username": "string",
"tweet_id": "string",
"content": "string",
"likes": number,
"reposts": number,
"replies": number,
"timestamp": "ISO_8601_string",
"query_used": "string"
}
[Start Scraping](https://bit.ly/3HvbvhM)
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