In the game Six Degrees of Kevin Bacon, perhaps the most widely-known application of network science principles, the goal is to find a link between a given actor and the actor Kevin Bacon. For example, Jon Hamm can be connected to Kevin Bacon as follows: Jon Hamm was in Bridesmaids with Rose Byrne, who was in X-Men: First Class, with Kevin Bacon. This game takes place on a network. In one version of the network, nodes represent actors and edges represent movies that two actors both appeared in. This version of the network (let's call it the actor-actor network) is sufficient for finding Kevin Bacon, but it doesn't fully represent the relationships between actors and movies. Movies typically have a cast of many actors, but each edge in the actor-actor network only corresponds to two actors. Consequently, there need to be many edges for each movie...
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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