Peper-Analysis

An intelligent analyzer and visualizer of natural language reviews from Airbnb and TripAdvisor.

Presentation

Peper Analysis Presentation

How to install and run the app?

We are using Python and JavaScript as main programming languages, so we will have to setup both sides in order to run the app.

Installation

1. Since our back-end is written using Node.js, you will need to download it from here.

2. Once you have Node.js you will need to install the packages we used to build this project, specified in package.json.
   Navigate to the root directory of the project and run the following:

   npm install

3. Now, that we are done with JavaScript's dependencies, lets continue with Python's. Of course you will need to download the Python programming language. You can do so from here.

4. Now, because we are using virtual environment to manage our dependencies, you will need to download Pipenv.
   Check out here to understand how to do so.

5. Once you have installed Pipenv you are ready to install the requirements specified in the Pipfile.
   Navigate to the root directory of the project and run the following:

   pipenv install

   Then run:
   If you are on Mac OSX / Linux:

   bash install.sh

   If you are on Windows:

   ./install.bat

6. Good Job! Now you are all setup to run the app.

Running

• Navigate to the root directory of the project and run the following:

  node index.js [path_to_the_python_executable]

• You can get your path_to_the_python_executable by running:

  pipenv --venv

This will return a path, if you are on Mac OSX / Linux add /bin/python, if you are on Windows add \\Scripts\\python to this path and this whole string pass to node index.js.

• For a shortcut you can try running this:
  Mac OSX / Linux:

  node index.js $(pipenv --venv)/bin/python

  Windows:

  node index.js $(pipenv --venv)\\Scripts\\python

Built With

• Node.js - JavaScript runtime built on Chrome's V8 JavaScript engine
• NumPy - Fundamental package for scientific computing with Python
• Pandas - Python Data Analysis Library
• NLTK - Natural Language Toolkit
• TextBlob - Simplified Text Processing
• Gensim - Topic modelling for humans

Authors

• Victor Velev - Initial work - VIVelev
• Kaloyan Madjunov - Initial work - kall0m
• Telerik Arsov - Initial work - NotGayBut5CentsAre5Cents
• Martin Datsev - Initial work - mdatsev
• Vladislav Georgiev - Initial work - VGeorgiev1
• Peter Milev - Initial work - Pe6oProgramista

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE file for details