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You're reading from  Network Science with Python and NetworkX Quick Start Guide

Product typeBook
Published inApr 2019
Reading LevelIntermediate
PublisherPackt
ISBN-139781789955316
Edition1st Edition
Languages
Python
Tools
NetworkX
Concepts
Data Science
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Author (1)
Edward L. Platt
Edward L. Platt
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Edward L. Platt

Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
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Summary

This chapter has described many different techniques for quantifying the large-scale structure of networks. Network size can be quantified using the diameter or mean shortest path. Global clustering can be used to quantify how likely a node's neighbors are to be neighbors with each other. Connectivity measures, such as the minimum or average node/edge connectivity, are calculated by finding minimum cuts, and quantify network resilience. The chapter concluded by showing how inequality measures such as entropy and the Gini index can be used to turn small-scale centrality measures into large-scale measures of network centralization. The next chapter discusses medium-scale network structures and community detection.

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Network Science with Python and NetworkX Quick Start Guide
Published in: Apr 2019Publisher: PacktISBN-13: 9781789955316
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Edward L. Platt

Edward L. Platt creates technology for communities and communities for technology. He is currently a researcher at the University of Michigan School of Information and the Center for the Study of Complex Systems. He has published research on large-scale collective action, social networks, and online communities. He was formerly a staff researcher at the MIT Center for Civic Media. He contributes to many free/open source software projects, including tools for media analysis, network science, and cooperative organizations. He has also done research on quantum computing and fault tolerance. He has an M.Math in Applied Mathematics from the University of Waterloo, as well as B.S degrees in both Computer Science and Physics from MIT.
Read more about Edward L. Platt

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