Bittooth

A senior project about Bitcoin value prediction.

Description

This project tries to create a model which predicts the value of bitcoin from both statistically analysis and Twitter sentiment on a given period of time. Many different models are designed and tested to see which gives the best results.

Below here is our project structure. One node corresponds to one notebook.

Installation

There are two method of installations: with or without virtual environment. You only need to install with virtual environment if you are a developer of the project.

Our project uses DVC to source control our data to Google Drive remote. Please refer to here for more information on pulling data.

Install without virtual environment

1. Install Twint.

   pip install --upgrade git+https://github.com/kevctae/twint.git

2. Install dependencies from requirements.txt.

   pip install -r ./setup/requirements.txt

3. Run Jupyter Notebook.

   jupyter notebook

Install with virtual environment (Development)

1. Install pyenv.
2. Install pyenv-virtualenv
3. Run setup script based on the OS:

   • (macOS) Allow executable on setup-mac.sh and run the script.

     cd ./setup
     chmod +x ./setup-mac.sh
     ./setup-mac.sh

Pulling data with DVC

In order to pull data from Google Drive, you will first need permission to access the Drive from kevctae. Once you have permision, you may pull data using command (make sure to install DVC from here):

dvc pull

It will ask you to get verification code on the first pull. Follow the provided URL and login to your Google account

Acknowledgement

• Twint
• TvDatafeed

Authors

• kevctae
• minchayisara
• pattanadeen
• Julian-Kota-Kikuchi