dataset_info dict | data list |
|---|---|
{
"dataset_name": "sam_altman_podcast_tweets_dataset",
"description": "Complete Twitter/X posts about Sam Altman podcast discussions, including OpenAI podcast announcements, Meta recruitment stories, GPT-5 discussions, and AGI debates. Each row represents a complete tweet with full metadata.",
"version": "1.0.0",
"license": "CC-BY-4.0",
"homepage": "https://huggingface.co/datasets/your-username/sam_altman_podcast_tweets",
"features": {
"id": {
"dtype": "string",
"description": "Original tweet ID from Twitter/X"
},
"content": {
"dtype": "string",
"description": "The full text content of the tweet"
},
"author": {
"dtype": "string",
"description": "Author field from tweet metadata"
},
"username": {
"dtype": "string",
"description": "Twitter/X username of the poster"
},
"user_id": {
"dtype": "string",
"description": "Twitter/X user ID"
},
"conversation_id": {
"dtype": "string",
"description": "ID of the conversation thread"
},
"created_at": {
"dtype": "string",
"description": "Timestamp when the tweet was created (ISO format)"
},
"likes": {
"dtype": "int32",
"description": "Number of likes on the tweet"
},
"possibly_sensitive": {
"dtype": "bool",
"description": "Whether the content is flagged as possibly sensitive"
},
"tweet_id": {
"dtype": "int64",
"description": "Numeric tweet ID"
},
"public_metrics": {
"dtype": "struct",
"description": "Engagement metrics for the tweet"
}
},
"splits": {
"train": {
"name": "train",
"num_examples": 76,
"num_bytes": 43839
}
},
"download_size": 43839,
"dataset_size": 43839,
"tags": [
"twitter",
"social-media",
"sam-altman",
"openai",
"gpt",
"ai",
"podcast",
"nlp"
]
} | [
{
"id": "1935448976754622573",
"content": "@povihendrix @OpenAI @sama @AndrewMayne The OpenAI Podcast, hosted by Andrew Mayne with Sam Altman, discusses AI's future. Key points: GPT-5 may launch by June 2025, with enhanced reasoning and autonomy, though timelines are uncertain. Altman claims AGI, defined as... |
🔍 X-Twitter Scraper: Real-Time Tweet Search & Scrape Tool
Search and scrape X-Twitter for posts by keyword, account, or trending topics.
A simple, no-code tool to pull real-time, relevant content in LLM-ready JSON format — perfect for agents, RAG systems, or content workflows.
👉 Start Searching & Scraping on Hugging Face
✨ Features
⚡ Real-Time Fetch
Stream the latest tweets as they’re posted — no delay.
🎯 Flexible Search
Search by keywords, #hashtags, $cashtags, @accounts, or trending topics.
📈 Engagement Metrics
Includes likes, replies, reposts, timestamps, and more.
🧩 LLM-Ready Output
Get clean JSON you can drop into any AI tool, agent, or pipeline.
💸 Free Tier
Up to 100 queries during beta. Customize up to 25 tweets per query.
🛠 How It Works
- Open the Scraper Tool
- Enter your query (
keyword,#hashtag,@user, etc.) and set tweet count - Click Search — our engine fetches tweets in real-time
- Copy or download your results in JSON format
- Plug it into your AI agent, RAG pipeline, or content workflow
🔥 Popular Use Cases
- 🧠 Sentiment & price prediction (crypto, stocks)
- 📊 Trend discovery & viral content tracking
- 🗞 News & political monitoring in real time
- 🧬 LLM training datasets
- 💡 Creative content inspiration
Get started now —
👉 Use the X-Twitter Scraper on Hugging Face
- Downloads last month
- 20