My interest in network science was, in part, inspired by my experience with hackerspaces and makerspaces. These spaces are member-run organizations that provide space and tools for do-it-yourself/technology/art projects. In 2009, I worked with several others in the Detroit area to start a space called i3 Detroit. During my time at i3 Detroit, I was struck by the creativity and innovation happening in i3 Detroit and other spaces, not just in the projects that were being created, but also in the unique types of volunteer-run, non-hierarchical organizations that were being developed. One of the keys to this innovation was the way ideas were spread within and between spaces. Ideas were spread from space to space by participants in national events and by members who went on hackerspace tours. Ideas were spread within spaces by the regulars who...
Network Science with Python and NetworkX Quick Start Guide
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Network Science with Python and NetworkX Quick Start Guide
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Overview of this book
NetworkX is a leading free and open source package used for network science with the Python programming language. NetworkX can track properties of individuals and relationships, find communities, analyze resilience, detect key network locations, and perform a wide range of important tasks. With the recent release of version 2, NetworkX has been updated to be more powerful and easy to use.
If you’re a data scientist, engineer, or computational social scientist, this book will guide you in using the Python programming language to gain insights into real-world networks. Starting with the fundamentals, you’ll be introduced to the core concepts of network science, along with examples that use real-world data and Python code. This book will introduce you to theoretical concepts such as scale-free and small-world networks, centrality measures, and agent-based modeling. You’ll also be able to look for scale-free networks in real data and visualize a network using circular, directed, and shell layouts.
By the end of this book, you’ll be able to choose appropriate network representations, use NetworkX to build and characterize networks, and uncover insights while working with real-world systems.
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Current Title:
Network Science with Python and NetworkX Quick Start Guide
Table of Contents (15 chapters)
Preface
Free Chapter
What is a Network?
Working with Networks in NetworkX
From Data to Networks
Affiliation Networks
The Small Scale - Nodes and Centrality
The Big Picture - Describing Networks
In-Between - Communities
Social Networks and Going Viral
Simulation and Analysis
Networks in Space and Time
Visualization
Conclusion
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