A First Course in Network Science

Edition: 1

Publication year: 2020

ISBN: 9781108471138

Buy: Amazon | Cambridge University Press

Authors

• Filippo Menczer, Indiana University, Bloomington
• Santo Fortunato, Indiana University, Bloomington
• Clayton A. Davis, Indiana University, Bloomington

Level

• Undergraduate
• Graduate

Subject Areas

• network science
• complexity
• statistical physics
• social networks
• computer science
• information science
• brain science
• political science
• communication
• management
• mathematics
• health
• financial networks
• biological networks

Abstract

Networks pervade all aspects of our lives: networks of friends, communication, computers, the Web, and transportation are examples we experience daily, while networks in our brain and cells determine our very survival. The network is a general yet powerful way to represent and study simple and complex relationships. Today, a basic understanding of network processes is required in job sectors from marketing to technology, from management to design, and from biology to the arts and humanities. This textbook is designed to introduces networks to a broad audience of undergraduate students from informatics, business, computer science and engineering, information science, biology, physics, statistics, and social sciences. After surveying networks in many areas, the book talks about the properties of social networks and the key role of hubs. Directed and weighted networks are discussed using the Web and the spread of information and misinformation in social media as case studies. The final chapters cover the more advanced topics of networks models, communities, and dynamics. No technical mathematical or programming background is required, making the book feasible for introductory courses at any level, including network literacy and programming literacy courses. However, the book includes optional technical sections for more advanced students. Programming tutorials, exercises, and datasets allow readers to gain and test their understanding through hands-on activities for building and analyzing networks.

Reviews & Endorsements

This is a book that truly takes in hand students from all backgrounds to discover the power of network science. It guides the readers through the basic concepts needed to enter the field, while providing at the same time the necessary programming rudiments and tools. Rigorous, albeit very accessible, this book is the ideal starting point for any student fascinated by the emerging field of network science.

--Alessandro Vespignani, Sternberg Distinguished Professor of Physics, Health, and Computer Sciences, Northeastern University

We cannot make sense of the world without learning about networks. This comprehensive and yet accessible text is an essential resource for all interested in mastering the basics of network science. Indispensable for undergraduate and graduate education, the book is also a much-needed primer for researchers across the many disciplines where networks are on the rise.

--Olaf Sporns, Distinguished Professor of Psychological and Brain Sciences, Indiana University

Buckle up! This book bounds ahead of the curve in teaching network science. Without formalism, but with remarkable clarity and insight, the authors use experiential learning to animate concepts, captivate students, and deliver skills for analyzing and simulating network data. This book will not only make students smarter, they will feel and act smarter.

--Brian Uzzi, Thomas Professor of Management, Northwestern University

A First Course in Network Science by Menczer, Fortunato, and Davis is an easy-to-follow introduction into network science. An accessible text by some of the best-known practitioners of the field, offering a wonderful place to start one's journey into this fascinating field, and its potential applications.

--Albert-László Barabási, Dodge Distinguished Professor of Network Science, Northeastern University

This is a timely book that comes from authorities in the field of Complex Networks. The book is very well written and represents the state of the art of research in the field. For these reasons, it represents both a reference guide for experts and a great textbook for the students.

--Guido Caldarelli, Professor of Theoretical Physics, Scuola IMT Alti Studi Lucca

The book by Menczer, Fortunato, and Davis, A First Course in Network Science, is an amazing tour de force in bringing network science concepts to the layman. It is an extraordinary book with which to start thinking about networks that nowadays represent the linchpins of our world.

--Alex Arenas, Professor of Computer Science and Mathematics, Universidad Rovira i Virgili

Should be titled the "Joy of Networks," clearly conveys the fun and power of the science of networks, while providing extensive hands-on exercises with network data.

--David Lazer, University Distinguished Professor of Political Science and Computer and Information Science, Northeastern University

If you are looking for a sophisticated yet introductory book on network analysis from a network science perspective, look no further. This is an excellent introduction that is also eminently practical, integrating exactly the right set of tools. I highly recommend it.

--Stephen Borgatti, Shellgren Chair of Management of Strategy, University of Kentucky

Table of Contents

0. Introduction

1. Basic Elements (Chapter 1 Tutorial)

2. Small Worlds (Chapter 2 Tutorial)

3. Hubs (Chapter 3 Tutorial)

4. Direction & Weights (Chapter 4 Tutorial)

5. Network Models (Chapter 5 Tutorial)

6. Communities (Chapter 6 Tutorial)

7. Dynamics (Chapter 7 Tutorial)

Appendix A - Python Tutorial

Appendix B - NetLogo

References

Index

A Note about Python, Tutorials, and Jupyter Notebooks

Our tutorials use Python 3 and NetworkX (2.4 or later). They are in the form of Jupyter Notebooks. To load, view, and run these tutorials, you can follow one or both of two approaches:

1. There are several free services to run Jupyter notebooks in the cloud at the time of this writing, including:

   • Google Colab
   • Binder
   • Kaggle Kernels
   • Azure Notebooks
   • Datalore
   • Gryd

   Each cloud-based notebook service has pros and cons and we cannot test them all extensively, so your mileage may vary. You may have to try more than one solution, read documentation, and/or seek support from the providers to install packages.

2. If you wish to run Python locally on your laptop, and don't have Jupyter/IPython installed on your machine, we recommend installing the Anaconda Python distribution with Python 3. This option requires that you are comfortable with managing software packages (i.e., using pip or conda). Local Python installations can present issues, especially on Windows machines. Packages are system dependent. In all cases, we are unable to provide support.

Additional Teaching Resources

• Dataset files

• Solutions to selected exercises (solutions to all exercises can be found on the textbook website for instructors)

• Sample slides (lecture slide decks for all chapters can be found on the textbook website for instructors)