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Practical social network analysis with Python

Author: Krishnaraj P M; Ankith Mohan; K G Srinivasa
Publisher: Cham, Switzerland : Springer, [2018]
Series: Computer communications and networks.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for  Read more...
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Genre/Form: Electronic books
Additional Physical Format: (OCoLC)1042085250
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Krishnaraj P M; Ankith Mohan; K G Srinivasa
ISBN: 9783319967462 3319967460
OCLC Number: 1050110412
Description: 1 online resource.
Contents: Intro; Preface; Network; Graph; Organization of the Book; Network Datasets; Contents; List of Figures; List of Tables; 1 Basics of Graph Theory; 1.1 Choice of Representation; 1.1.1 Undirected Graphs; 1.1.2 Directed Graphs; 1.2 Degree of a Vertex; 1.3 Degree Distribution; 1.4 Average Degree of a Graph; 1.5 Complete Graph; 1.6 Regular Graph; 1.7 Bipartite Graph; 1.8 Graph Representation; 1.8.1 Adjacency Matrix; 1.8.2 Edge List; 1.8.3 Adjacency List; 1.9 Edge Attributes; 1.9.1 Unweighted Graph; 1.9.2 Weighted Graph; 1.9.3 Self-looped Graph; 1.9.4 Multigraphs; 1.10 Path; 1.11 Cycle 1.12 Path Length1.13 Distance; 1.14 Average Path Length; 1.15 Diameter; 1.16 Connectedness of Graphs; 1.17 Clustering Coefficient; 1.18 Average Clustering Coefficient; Reference; 2 Graph Structure of the Web; 2.1 Algorithms; 2.1.1 Breadth First Search (BFS) Algorithm; 2.1.2 Strongly Connected Components (SCC) Algorithm; 2.1.3 Weakly Connected Components (WCC) Algorithm; 2.2 First Set of Experiments-Degree Distributions; 2.3 Second Set of Experiments-Connected Components; 2.4 Third Set of Experiments-Number of Breadth First Searches; 2.5 Rank Exponent mathcalR; 2.6 Out-Degree Exponent mathcalO 2.7 Hop Plot Exponent mathcalH2.8 Eigen Exponent mathcalE; References; 3 Random Graph Models; 3.1 Random Graphs; 3.2 Erdös-Rényi Random Graph Model; 3.2.1 Properties; 3.2.2 Drawbacks of Gn,p; 3.2.3 Advantages of Gn,p; 3.3 Bollobás Configuration Model; 3.4 Permutation Model; 3.5 Random Graphs with Prescribed Degree Sequences; 3.5.1 Switching Algorithm; 3.5.2 Matching Algorithm; 3.5.3 ``Go with the Winners'' Algorithm; 3.5.4 Comparison; References; 4 Small World Phenomena; 4.1 Small World Experiment; 4.2 Columbia Small World Study; 4.3 Small World in Instant Messaging; 4.4 Erdös Number 4.5 Bacon Number4.6 Decentralized Search; 4.7 Searchable; 4.8 Other Small World Studies; 4.9 Case Studies; 4.9.1 HP Labs Email Network; 4.9.2 LiveJournal Network; 4.9.3 Human Wayfinding; 4.10 Small World Models; 4.10.1 Watts-Strogatz Model; 4.10.2 Kleinberg Model; 4.10.3 Destination Sampling Model; References; 5 Graph Structure of Facebook; 5.1 HyperANF Algorithm; 5.2 Iterative Fringe Upper Bound (iFUB) Algorithm; 5.3 Spid; 5.4 Degree Distribution; 5.5 Path Length; 5.6 Component Size; 5.7 Clustering Coefficient and Degeneracy; 5.8 Friends-of-Friends; 5.9 Degree Assortativity 5.10 Login Correlation5.11 Other Mixing Patterns; 5.11.1 Age; 5.11.2 Gender; 5.11.3 Country of Origin; References; 6 Peer-To-Peer Networks; 6.1 Chord; 6.2 Freenet; Problems; References; 7 Signed Networks; 7.1 Theory of Structural Balance; 7.2 Theory of Status; 7.3 Conflict Between the Theory of Balance and Status; 7.4 Trust in a Network; 7.4.1 Atomic Propagations; 7.4.2 Propagation of Distrust; 7.4.3 Iterative Propagation; 7.4.4 Rounding; 7.5 Perception of User Evaluation; 7.6 Effect of Status and Similarity on User Evaluation; 7.6.1 Effect of Similarity on Evaluation
Series Title: Computer communications and networks.
Responsibility: Krishna Raj P.M., Ankith Mohan, K.G. Srinivasa.

Abstract:

This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the  Read more...

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