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How to beat terrorism efficiently: identification of set of key players in terrorist networks

Network Tour of Data Science, 2018, EPFL

This is the directory of the project for the course "A Network Tour of Data Science" fall 2018, EPFL. This file contains practical information on the project implementation and how to run it. For more detailed explanation of the project (goals, implemented algorithms, ...), please refer to the report (Report.pdf).

The purpose of this project is to learn various vulnerable points of a terrorist network by identifying a set of key players whose roles are vital to the success of such organizations. We seek to develop an appropriate methodology to evaluate the importance of each terrorist to the effectiveness of the network as a whole, and identify an optimal set of key terrorists that we recommend should be targeted in order to debilitate the network.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

The required environment for running the code and reproducing the results is a computer with a valid installation of Python 3. More specifically, Python 3.6 is used.

Besides that (and the built-in Python libraries), the following packages are used and have to be installed:

Installing

To install the previously mentioned libraries a requirements.txt file is provided. The user is free to use it for installing the previously mentioned libraries.

Project Structure

The project has the following folder (and file) structure:

How to execute the files.

Only fragmentation and information flow Notebooks are intended to be executed. All other files do not provide any directly readable result. The project has been developed so that fragmentation notebook is read first as it contains an initial exploration of the data. Nevertheless, information_flow notebook can be read and understood without need of previous consultation to the fragmentation notebook, taking into account the reader is aware of the purpose of the project.

Authors

License

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