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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
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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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Adding edge weights

So far, all of the edges in this chapter have been unweighted, but the Graph class also supports weighted edges. Edge weights are handy when connections can have different strengths and when there is a way to quantify the strength of a connection; for example, how often two friends talk to each other, the volume of fluid a pipe can transport, or the number of direct flights between two cities.

The karate club network doesn't have any additional information about the strength of the edges, but there are relevant properties of those edges that can be calculated, such as the tie strength. Tie strength increases with the number of neighbors that two nodes have in common. It is motivated by the observation that closer friends tend to have more friends in common, and it can often reveal insight into the structure of a social network. The following code calculates...

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Network Science with Python and NetworkX Quick Start Guide
Published in: Apr 2019Publisher: PacktISBN-13: 9781789955316

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