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Using NLTK to analyze the trending Meta from recent Pump.Fun launch, applying sentiment analysis and time series analysis to capture current meme hype

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🚀 Pump.Fun Token Sentiment Analyzer

📊 Project Overview

Pump.Fun Sentiment Analysis is an advanced real-time token analysis tool that provides deep insights into the latest tokens on the Pump.Fun platform.

✨ Key Features

🔍 Real-Time Data Extraction

  • Asynchronous API calls to Pump.Fun
  • Continuous token data retrieval
  • Comprehensive market tracking

📈 Advanced Sentiment Analysis

  • Multi-source sentiment scoring
  • Comment and trading pattern analysis
  • Market cap trend detection

🤖 Automated Notifications

  • Telegram integration
  • Real-time token trend updates
  • Instant market insights

🛠 Tech Stack

Python Telegram Async

  • Data Processing: Pandas, aiohttp
  • NLP: TextBlob, spaCy
  • Visualization: Matplotlib
  • Notifications: Telegram Bot

🚀 Quick Start

### Prerequisites
- Python 3.8+
- Telegram Bot Token
- Pump.Fun API Access

### Installation
```bash
git clone https://github.com/your-username/pump-meta.git
cd pump-meta
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Configuration

  1. Replace your-telegram-token in config.py
  2. Set up Telegram group ID

Run

python3 main.py
Screenshot 2024-12-12 at 14 53 44

🔮 Future Roadmap

  • Machine Learning Trend Prediction
  • Interactive Web Dashboard
  • Advanced Backtesting Capabilities
  • Multi-Platform Integration

📈 Project Methodology

  1. Data Collection: Asynchronous API Retrieval
  2. Sentiment Analysis: Multi-Source Scoring
  3. Trend Detection: NLP-Powered Insights
  4. Notification: Real-Time Telegram Updates

📜 License

Distributed under the MIT License. See LICENSE for more information.

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Using NLTK to analyze the trending Meta from recent Pump.Fun launch, applying sentiment analysis and time series analysis to capture current meme hype

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