The Financial News Article Summarizer is a Python-based solution that extracts insights and analyzes sentiment from financial news articles. It provides a summary of the article and an indication of the overall sentiment (positive, negative, or neutral) of the text.

This project was built using the following technologies and libraries:

• Python 3
• newspaper library for article extraction and natural language processing
• TextBlob library for sentiment analysis
• nltk library for additional natural language processing functionality

If you would like to contribute to this project, please feel free to open an issue or submit a pull request. I welcome contributions of all kinds, from bug fixes to feature enhancements.

This project is licensed under the MIT License. See LICENSE for more information.

This project was inspired by the need for a simple and effective way to extract insights from financial news articles. I am grateful to the developers of the newspaper, TextBlob, and nltk libraries for their contributions to this project.