- "This book is an excellent read for anyone who wants to learn the fundamentals of complex network analysis with a focus on application. The case studies cover a variety of topics and help readers link concepts to applications, providing readers with a clear, well-structured, hands-on experience that deepens their understanding of the concepts without requiring Python programming experience." - Kate Li, Ph.D., Associate professor, Sawyer Business School, Suffolk University
- "As a social scientist interested in network analysis but having limited knowledge of Python, I found the book very useful. The author explains technical problems in a way that is easy to understand for non-computer scientists. It is a great introduction for those interested in network analysis seeking to apply the method in their research." - Weiqi Zhang, Associate professor of government, Suffolk University
- "Complex Network Analysis in Python is a thorough introduction to the tools and techniques needed for complex network analysis. Real-world case studies demonstrate how one can easily use powerful Python packages to analyze large networks and derive meaningful analytic insights." - Mike Lin, Senior software engineer, Fugue Inc.
- "Having a deep understanding of complex network analysis is hard; however, this book will help you learn the basics to start mastering the skills you need to analyze complex networks, not only at a conceptual level but also at a practical level, by putting the theory into action using the Python programming language." - Jose Arturo Mora, Head of information technology and innovation, BNN Mexico
- "Complex networks have diverse applications in various fields, including healthcare, social networks, and machine learning. I found this book to be an excellent and comprehensive resource guide for researchers, students, and professionals interested in applying complex networks." - Rajesh Kumar Pandey, Graduate student, IIT Hyderabad
About the Author
Dmitry Zinoviev has graduate degrees in physics and computer science with a PhD from Stony Brook University. His research interests include computer simulation and modeling, network science, network analysis, and digital humanities. He has been teaching at Suffolk University in Boston, MA since 2001. He is the author of Data Science Essentials in Python.