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Network Science with Python and NetworkX Quick Start Guide

Network Science with Python and NetworkX Quick Start Guide

By : Platt
5 (3)
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Network Science with Python and NetworkX Quick Start Guide

Network Science with Python and NetworkX Quick Start Guide

5 (3)
By: Platt

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.
Table of Contents (15 chapters)
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Social networks

The defining feature of social networks is that nodes represent people. The networks themselves can represent anything from small informal friend groups to entire societies.

Edges in a social network represent a type of relationship between people. Often, this relationship is friendship or communication. However, it can also be something as abstract as the similarity in their video streaming behavior. Just imagine; you might never have met someone, but you could be the only two people in the world who enjoy watching videos of sleeping hippos. That is certainly a kind of relationship!

Many of the tools of network science come from the study of social networks in sociology. The sociologists, Jacob L. Moreno and Helen Hall Jennings, developed the techniques of sociometry, a precursor to modern social network analysis and network science (Moreno And Jennings, 1934...

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