Simple Sentiment Text Analysis is a Python web application built with Streamlit, designed for analyzing the sentiment of text data. It provides users with the ability to input either a URL of an article or directly enter text for sentiment analysis. The application extracts the text, generates a summary, and performs sentiment analysis on the input data.
- Text Summarization: Utilizes NLTK to generate a summary of the input text based on word frequencies.
- Sentiment Analysis: Employs NLTK's Vader Sentiment Analyzer to determine the sentiment polarity of the input text.
- Web Scraping: Allows users to input a URL to fetch the text content from a webpage for analysis.
- User-friendly Interface: Implemented using Streamlit, providing an intuitive and interactive user experience.
To run the application locally, follow these steps:
-
Clone the repository:
git clone https://github.com/laibashakil/simple-sentiment-text-analysis.git -
Navigate to the project directory:
cd simple-sentiment-text-analysis -
Install the dependencies:
pip install -r requirements.txt -
Run the Streamlit app:
streamlit run app.py -
Access the application in your browser at
http://localhost:8501.
Once the application is running, users can interact with it through a web interface. Here's how to use the application:
- Choose Input Option: Select whether to input a URL or text directly.
- Enter Input: Depending on the selected option, provide a URL or text input.
- Analyze: Click on the "Analyze" button to generate the summary and sentiment analysis results.
The project relies on the following Python packages:
- Streamlit
- Requests
- Beautiful Soup
- NLTK
These dependencies are listed in the requirements.txt file for easy installation.
Contributions to the project are welcome! If you have any ideas for improvements, new features, or bug fixes, please open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for more information.