## Project Title: Behavioral, Emotional, and Decision Data Survey

## Description
This project focuses on developing and utilizing advanced data-driven methodologies to model and influence human behavior, emotions, and decision-making processes. The aim is to obtain insights regarding the potential customer demand of using a patented quantum data architecture for organic and synthetic data labeling for ML/RL. This survey integrates, NLP, and sentiment analysis to improve interaction outcomes and improve robustness of discovery data collected. This repository contains a web application for conducting a survey focused on customer discovery. 

## Features

- **Questionnaire Interface:** Users can interact with the web application to answer a series of questions related to their organization's use of AI and data for content creation and deployment.
- **Sentiment Analysis:** Text responses provided by users are analyzed for sentiment (positive, neutral, negative) to provide insights into the level of enthusiasm for adopting this technology.
- **Results Interpretation:** Based on questionnaire responses and sentiment analysis, the application provides an overall score reflecting the potential demand the organization would have for i* data products.

## Technologies Used

- **Python:** Backend logic and sentiment analysis are implemented using Python programming language.
- **Streamlit:** The web application is built using Streamlit, a Python library for creating interactive web applications.
- **Pandas:** Data manipulation and analysis are performed using the Pandas library.
- **TextBlob** Natural Language Processing (NLP) Libraries: used for sentiment analysis.

## Usage

1. Clone the repository to your local machine.
2. Install the required dependencies listed in `requirements.txt`.
3. Run the application using the command `streamlit run survey.py`.
4. Access the application in your web browser and complete the questionnaire.
5. Review the interpreted results based on your responses and sentiment analysis.

## Contributors

- Marcus C. Rodriguez (https://github.com/marcuscrodriguez/survey): Developer
- Dr. Richard Conner
- Dr. Daniel Winterhalter

## License

This project is licensed under the [MIT License] (https://github.com/git/git-scm.com/blob/main/MIT-LICENSE.txt).

## Acknowledgements

- Special thanks to [Streamlit](https://streamlit.io/) for providing an easy-to-use framework for building web applications with Python.