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Network analysis literacy : a practical approach to network analysis project design
Zweig K., Springer International Publishing, New York, NY, 2016. 400 pp. Type: Book (978-3-709107-40-9)
Date Reviewed: Feb 1 2018

Networks are not just an important part of computer science--they are an important part of our daily lives. Many structures in nature and in our daily lives exhibit network behavior. For instance, our friendships can be seen as a network with many nodes and edges. With the rising importance of big data, network analytics--which is in the intersection of these two fields--has become important.

The book has 15 chapters. The first chapter “gives [an] overview of what network analysis does and why it is considered to be [important].” The second chapter “introduce[s] the main perspectives of the [three] fields that are at the core of complex network analysis: graph theory, sociology, and physics.” Chapter 3 introduces definitions such as bipartite graphs. Chapter 4 is about common network measures such as network transitivity. Chapter 5 covers network representations of complex systems. Chapters 6 and 7 are about random graphs and network models. Chapter 8 is about understanding and designing network measures. Chapter 9 is about centrality indices. Chapter 10 covers general problems with data. Chapter 11 is about relationships and relations, and includes examples of networks such as disease networks. Chapter 12 is about explanatory network models. Chapter 13 is about null models. Chapter 14 is on interpreting networks, and chapter 15 covers ethics in network analysis.

The book is a good source for researchers, network experts, and scientists studying network analytics. There can be many methods for different projects. It briefly goes over available methods and R and Python libraries to perform network analysis. It can also be used as a textbook in graduate classes. There are exercises and further reading sections at the end of each chapter, which will be useful to instructors. The book will also help readers understand how to think in a network analytics discipline.

Reviewer:  Gulustan Dogan Review #: CR145822 (1805-0182)
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