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Description

This tool is for detection of collusive users in Online Social Networks. The tool is developed and maintained by LCS2 Research Group at Indraprastha Institute of Information Technology, Delhi.


Project Structure

├── Procfile
├── Procfile.dev
├── README.md
├── app.py
├── config.py
├── error.log
├── forms.py
├── models.py
├── requirements.txt
├── static
│   ├── css
│   │   ├── bootstrap-3.0.0.min.css
│   │   ├── bootstrap-theme-3.0.0.css
│   │   ├── bootstrap-theme-3.0.0.min.css
│   │   ├── font-awesome-3.2.1.min.css
│   │   ├── layout.forms.css
│   │   ├── layout.main.css
│   │   ├── main.css
│   │   ├── main.quickfix.css
│   │   └── main.responsive.css
│   ├── font
│   │   ├── FontAwesome.otf
│   │   ├── fontawesome-webfont.eot
│   │   ├── fontawesome-webfont.svg
│   │   ├── fontawesome-webfont.ttf
│   │   └── fontawesome-webfont.woff
│   ├── ico
│   │   ├── apple-touch-icon-114-precomposed.png
│   │   ├── apple-touch-icon-144-precomposed.png
│   │   ├── apple-touch-icon-57-precomposed.png
│   │   ├── apple-touch-icon-72-precomposed.png
│   │   └── favicon.png
│   ├── img
│   └── js
│       ├── libs
│       │   ├── bootstrap-3.0.0.min.js
│       │   ├── jquery-1.10.2.min.js
│       │   ├── modernizr-2.6.2.min.js
│       │   └── respond-1.3.0.min.js
│       ├── plugins.js
│       └── script.js
└── templates
    ├── errors
    │   ├── 404.html
    │   └── 500.html
    ├── forms
    │   ├── forgot.html
    │   ├── login.html
    │   └── register.html
    ├── layouts
    │   ├── form.html
    │   └── main.html
    └── pages
        ├── placeholder.about.html
        └── placeholder.home.html

Quick Start

  1. Clone the repo
$ git clone https://github.com/hridaydutta123/collusive-user-detection-tool.git
$ cd collusive-user-detection-tool
  1. Initialize and activate a virtualenv:
$ virtualenv --no-site-packages env
$ source env/bin/activate
  1. Install the dependencies:
$ pip install -r requirements.txt
  1. Run the development server:
$ python app.py
  1. Navigate to http://localhost:5000

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  • Python 95.8%
  • Makefile 4.2%