Building better online reviews to empower users.
Authors: Brendan Davis, Carson Newton, and Marco Zangari
We analyze online reviews to empower users. Online reviews are helpful except when they are not. We aim to make sure that before you read a site's reviews you receive a comprehensive review-score to know whether you should spend your time at the site's reviews or not.
Point your browser at the site: Review Improve.
Hosting on AWS EC2 Amazon Webservice - S3 RDS PostGres
Automate updating your EC2 instance: Ansible
A dynamic Python webframework to manage all your modules: Django
Frontend web service with ready-to-use html and css: Bootstrap
Favicon created with: favicongenerator
The main language used: Python3.6
Scraped the web with: Beautiful Soup
Analyzed the data with: Used the natural language toolkit - Nltk And also the scikit for handling our classification models - scikit-learn
To add more categories beyond movies is a goal of ReviewImprove. We aim to be a clearing house for analyzing online reviews.
If you want to contribute, fork the repo: Review Improve Repo.
Make a directory to do your testing work. You can name it whatever you want, but here we name it review-improve. Once you've made your directory, enter the new directory:
mkdir reviewimprove-environment && cd reviewimprove-environment
Make your virtual environment for your testing suite and create its file system by activating it:
python -m venv ENV && source ENV/bin/activate
Install pytest:
pip install pytest
To read more: Pytest
Install pytest coverage:
pip install pytest-cov
To read more: Pytest-cov
You can deactivate your environment at any time by simply typing in your command line:
deactivate