Social Network Analysis

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SOCIAL NETWORK ANALYSIS
As social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose.
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..Figure 11.4 Visualizing the symmetric social network created by using NetworkX.Figure 11.5 Python program for creating the asymmetric social network using Netw...Figure 11.6 Visualizing the asymmetric social network created by using NetworkX.Figure 11.7 Python program for creating an asymmetric social network by applying...Figure 11.8 Visualizing the asymmetric social network created after applying the...Figure 11.9 Implementing the weighted social network using NetworkX.Figure 11.10 Displaying the weighted network in the form of circular architectur...Figure 11.11 Developing the multigraph for social networks using G_graph.edges (...Figure 11.12 Results collected using the G_graph.edges () method.Figure 11.13 Degree of a node for symmetric social network.Figure 11.14 Clustering and average clustering of a node for symmetric graph.Figure 11.15 Calculating shortest path and shortest path length of a node.Figure 11.16 Implementing the breadth-first search algorithm for User C.Figure 11.17 Implementing the breadth-first search algorithm for User A.Figure 11.18 Eccentricity distribution of a node in a graph using the nx.eccentr...Figure 11.19 Centrality by Eigenvector using NetworkX () function.Figure 11.20 Nodes with a high degree of betweenness centrality.Figure 11.21 Closeness to all other nodes is displayed for the G_symmetric graph...Figure 11.22 Loading necessary packages and the dataset.Figure 11.23 Function info () to display the dataframe’s contents.Figure 11.24 Function info () to illustrate the nodes and edges in the data set.Figure 11.25 Degree_centrality () and nx.degree () functions.Figure 11.26 Average shortest path calculation between two networks.Figure 11.27 The draw_networkx () method to visualize the facebook data set.Figure 11.28 The visual representation of the facebook data set with draw_networ...Figure 11.29 Python code for betweenness_centrality ().Figure 11.30 The visual representation of the data set with betweenness_centrali...Figure 11.31 The sorted() method displays the nodes with the centrality.Figure 11.32 PageRank() method to estimate popularity.Figure 11.33 Popularity nodes according to the page rank() method.

Guide

1 Cover

2 Table of Contents

3 Title Page

4 Copyright

5 Preface

6 Begin Reading

7 Index

8 End User License Agreement

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Scrivener Publishing

100 Cummings Center, Suite 541J

Beverly, MA 01915-6106

Publishers at Scrivener

Martin Scrivener ( martin@scrivenerpublishing.com)

Phillip Carmical ( pcarmical@scrivenerpublishing.com)

Social Network Analysis

Theory and Applications

Edited by

Mohammad Gouse Galety

Chiai Al Atroshi

Bunil Kumar Balabantaray

and

Sachi Nandan Mohanty

This edition first published 2022 by John Wiley Sons Inc 111 River Street - фото 1

This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA

© 2022 Scrivener Publishing LLC

For more information about Scrivener publications please visit www.scrivenerpublishing.com.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

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For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.

Limit of Liability/Disclaimer of WarrantyWhile the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials, or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read.

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