https://github.com/jalfr3d/sentiment-analysis-webapp

A sentiment analysis plotted in a webapp using streamlit and journals entries, it show the positivity or negativity for every entry
https://github.com/jalfr3d/sentiment-analysis-webapp

nltk-python plotly-python plotting python sentiment-analysis streamlit webapp

Last synced: about 2 months ago
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A sentiment analysis plotted in a webapp using streamlit and journals entries, it show the positivity or negativity for every entry

• Host: GitHub
• URL: https://github.com/jalfr3d/sentiment-analysis-webapp
• Owner: jalfr3d
• License: mit
• Created: 2023-04-28T20:36:25.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2023-11-07T20:22:29.000Z (about 1 year ago)
• Last Synced: 2023-11-08T05:38:47.880Z (about 1 year ago)
• Topics: nltk-python, plotly-python, plotting, python, sentiment-analysis, streamlit, webapp
• Language: Python
• Homepage:
• Size: 9.77 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Sentiment Analysis Web App

Is a web application built using Streamlit for performing sentiment analysis on journal entries. It analyzes the sentiment of your diary entries, helping you understand the positivity or negativity of your thoughts over time.

## Features

- **Sentiment Analysis**: Analyze the sentiment of your journal entries, providing insights into the emotional tone of your writing.

- **Visualization**: Visualize the positivity and negativity scores over time with interactive line charts.

- **Customization**: Customize the web app, add more visualizations, or extend the functionality as per your preferences.

## Prerequisites

- Python 3.x

- Install the required Python libraries using pip:

  ```bash

  pip install streamlit plotly nltk

  

## Usage

1. Clone the repository to your local machine.

2. Place your journal entries in the 'diary' folder. Entries should be in individual text files.

3. Run the Streamlit web application using the following command:

   ```bash

   streamlit run main.py

4. Access the web app in your browser at the provided URL.

5. The web app will display line charts showing the positivity and negativity scores of your journal entries over time.

6. Gain insights into the emotional tone of your writing and how it evolves.

## Customization and Extension

- You can further customize the web app's design and layout by editing the Streamlit script.

- Enhance the sentiment analysis with additional natural language processing (NLP) techniques or visualizations.

- Integrate the web app with a database to store and retrieve journal entries securely.

- Deploy the web app to a server or cloud platform to make it accessible online.

## License

This project is licensed under the MIT License. You are free to use and modify the code for your own purposes.