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Working with Network Data

Working with Network Data

Working with Network Data

A Data Science Perspective

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James Bagrow, University of Vermont, Yong‐Yeol Ahn, Indiana University, Bloomington

Publisher:: Cambridge University Press
Online publication date:: June 2024
Print publication year:: 2024
Online ISBN:: 9781009212601
DOI:: https://doi.org/10.1017/9781009212601

Subjects:: Physics and Astronomy, Knowledge Management, Databases and Data Mining, Computer Science, Statistical Physics

58.34 (EUR)

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Contents

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Contents

Select Frontmatter

Frontmatter
pp i-iv
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Select Contents

Contents
pp v-x
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Select Preface

Preface
pp xi-xiv
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Select Part I - Background

Part I - Background
pp 1-2
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Select Chapter 1 - A whirlwind tour of network science

Chapter 1 - A whirlwind tour of network science
pp 3-16
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Select Chapter 2 - Network data across fields

Chapter 2 - Network data across fields
pp 17-26
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Select Chapter 3 - Data ethics

Chapter 3 - Data ethics
pp 27-38
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Select Chapter 4 - Primer

Chapter 4 - Primer
pp 39-62
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Select Part II - Applications, tools, and tasks

Part II - Applications, tools, and tasks
pp 63-64
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Select Chapter 5 - The life cycle of a network study

Chapter 5 - The life cycle of a network study
pp 65-72
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Select Chapter 6 - Gathering data

Chapter 6 - Gathering data
pp 73-82
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Select Chapter 7 - Extracting networks from data — the “upstream task”

Chapter 7 - Extracting networks from data — the “upstream task”
pp 83-88
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Select Chapter 8 - Implementation: storing and manipulating network data

Chapter 8 - Implementation: storing and manipulating network data
pp 89-104
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Select Chapter 9 - Incorporating node and edge attributes

Chapter 9 - Incorporating node and edge attributes
pp 105-116
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Select Chapter 10 - Awful errors and how to amend them

Chapter 10 - Awful errors and how to amend them
pp 117-136
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Select Chapter 11 - Explore and explain: statistics for network data

Chapter 11 - Explore and explain: statistics for network data
pp 137-164
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Select Chapter 12 - Understanding network structure and organization

Chapter 12 - Understanding network structure and organization
pp 165-202
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Select Chapter 13 - Visualizing networks

Chapter 13 - Visualizing networks
pp 203-222
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Select Chapter 14 - Summarizing and comparing networks

Chapter 14 - Summarizing and comparing networks
pp 223-234
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Select Chapter 15 - Dynamics and dynamic networks

Chapter 15 - Dynamics and dynamic networks
pp 235-250
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Select Chapter 16 - Machine learning

Chapter 16 - Machine learning
pp 251-278
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Select Interlude — Good practices for scientific computing

Interlude — Good practices for scientific computing
pp 279-282
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Select Chapter 17 - Research record-keeping

Chapter 17 - Research record-keeping
pp 283-288
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Select Chapter 18 - Data provenance

Chapter 18 - Data provenance
pp 289-292
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Select Chapter 19 - Reproducible and reliable code

Chapter 19 - Reproducible and reliable code
pp 293-300
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Select Chapter 20 - Helpful tools

Chapter 20 - Helpful tools
pp 301-314
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Select Part III - Fundamentals

Part III - Fundamentals
pp 315-316
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Select Chapter 21 - Networks demand network thinking: the friendship paradox

Chapter 21 - Networks demand network thinking: the friendship paradox
pp 317-326
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Select Chapter 22 - Network models

Chapter 22 - Network models
pp 327-350
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Select Chapter 23 - Statistical models and inference

Chapter 23 - Statistical models and inference
pp 351-376
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