🚀 LexiScrape – Web Scraping & NLP Text Analyzer

LexiScrape is a Python-based project that combines Web Scraping and Natural Language Processing (NLP) to extract, clean, and analyze textual data from web pages. This project demonstrates a complete mini NLP pipeline — from raw HTML data to meaningful insights.

---

🌐 Key Features

• 🔍 Extracts real-time data from websites (Wikipedia)
• 🧾 Parses HTML content using BeautifulSoup
• 🔤 Tokenizes raw text into meaningful words
• 🧹 Removes stopwords using NLTK
• 📊 Performs word frequency analysis
• 📈 Visualizes top frequent words using graphs

---

🛠️ Tech Stack

• Python
• BeautifulSoup (bs4)
• NLTK (Natural Language Toolkit)
• Matplotlib
• HTML5lib

---

⚙️ Project Workflow

1. 🌐 Fetch web content from a URL
2. 🧾 Parse HTML and extract text
3. 🔤 Tokenize text into words
4. 🧹 Remove unnecessary stopwords
5. 📊 Compute word frequency distribution
6. 📈 Visualize top frequent words

---

📂 Project Structure

LexiScrape/
│── main.py
│── README.md
│── requirements.txt
│── .gitignore

---

▶️ How to Run

1️⃣ Clone the Repository

git clone https://github.com/selvan-01/LexiScrape.git
cd LexiScrape

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Run the Project

python main.py

---

📊 Output

• Displays a graph of the Top 50 Most Frequent Words
• Helps identify key terms and patterns from web content

---

💡 Use Cases

• Text Analysis & Keyword Extraction
• Data Science & NLP Learning
• Content Analysis
• Web Data Mining

---

🚀 Future Enhancements

• 🌍 Support multiple websites dynamically
• 🤖 Add sentiment analysis
• 🧠 Use advanced NLP models (SpaCy / Transformers)
• 🌐 Build a web interface (Flask / Streamlit)

---

📌 Conclusion

LexiScrape is a beginner-friendly yet powerful project that showcases how web data can be transformed into meaningful insights using NLP techniques.

---

🔗 Links

• 💼 LinkedIn
• 🌍 Portfolio
• 💻 GitHub

⭐ If you found this project useful, consider giving it a star!