# Do They?

This repository contains a web application for conducting a survey. The questionnaire aims to assess various aspects of romantic relationships, including behaviors, emotions, and decisions/thoughts, through a series of questions and sentiment analysis of collected quantitative and qualitative data.

## Features

- **Questionnaire Interface:** Users can interact with the web application to answer a series of questions related to their relationship.
- **Sentiment Analysis:** Text responses provided by users are analyzed for sentiment (positive, neutral, negative) to provide insights into relationship dynamics.
- **Results Interpretation:** Based on questionnaire responses and sentiment analysis, the application provides interpretations and an overall score taking into consideration different aspects of the relationship.

## 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 dothey.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/dothey): Developer

## License

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

## Acknowledgements

- This project is inspired by the work of psychologists and relationship experts in assessing and understanding romantic relationships. 
A special thanks to Dr. Richard Conner for his inspirational work in this field.
- Also a special thanks to [Streamlit](https://streamlit.io/) for providing an easy-to-use framework for building web applications with Python.