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Article Analyzer

This project analyzes the sentiment of news articles using Natural Language Processing (NLP) techniques. It fetches articles from provided URLs, summarizes them, and determines their sentiment (positive, negative, or neutral).

Features

  • Fetch articles from URLs
  • Summarize articles
  • Analyze sentiment of articles
  • Display results in a modern Tkinter GUI
  • Send analysis results via email
  • Project Setup
  • To set up the project and install the required dependencies, follow these steps:

Steps to Install

Clone the Repository:

git clone https://github.com/csana004/Article-Analyzer.git
cd Article-Analyzer

Install the Dependencies:

Ensure you have pip installed. Then, run the following commands:

pip install nltk
pip install textblob
pip install newspaper3k

Download NLTK Data:

The project uses the punkt tokenizer. To download it, run the following Python command:

import nltk
nltk.download('punkt')

Run the Application:

Once the dependencies are installed, you can run the application using:

python article_analyzer.py

Usage

Enter the Article URL:

Open the application and enter the URL of the article you want to analyze.

Fetch and Analyze:

Click on the "Fetch and Analyze" button to fetch the article, summarize it, and analyze its sentiment.

View Results:

The title, authors, publication date, summary, and sentiment of the article will be displayed in the GUI.