A First Course in Network Science

I enjoyed reading this textbook for many reasons which are summarized below. I highly recommend it for teaching intro. to network science courses to sophomore/junior students (Chapters 0 -- 4), as well as senior/graduate students (Chapters 5 -- 7). I currently use it to teach Intro. to Network Science to undergraduates. * Clear and concise: Overall, the writing is clear and approachable. Mathematical formalism are unpacked and explained. The textbook is not long, but surprisingly packs a lot of information. * Real-world examples and real-world problems: From online social networks to transportation networks, throughout the textbook, concepts are explained with real-world examples, thus. making the abstract ideas relatable. Additionally, when discussion social networks, the writers explore important challenges (misinformation diffusion and echo chambers) plaguing online social networks. * Info-boxes: You'd learn more than network science in this textbook. I really appreciate how the authors included important ideas in info-boxes. For example, an info-box summarized why the logarithm scale is useful in visualization very small and very large quantities in the same plot. * Code examples: Documented-code examples are provided across all chapters. And the textbook provides a Github repo with documented Python notebooks. * Progression: The progression of the textbook is well-thought out: Chapter 0 (introduction) inspires you to continue reading by showing the broad applicability of network science. Chapter 1 (Network elements), takes you on a tour to visit important network concepts. Chapters 2 -- 4 (Small worlds, Hubs, and Direction & Weights) focus on important concepts that are prominent in many real-world networks. Chapters 5 -- 7 (Network models, communities, and dynamics) explores more advanced concepts. Overall the textbook strikes the right balance between fundamental/introductory materials and advanced concepts.

I love this book. Nice color visuals, smooth pages that smell good. The content? Oh, sorry about the tangent. I should mention that the author does a fantastic job of presenting this material and separates the technical (math and its notation) from the non-technical material so those not interested in the more complex details can continue reading. Presentation is clear and concise. The coverage of python's networkx package is clear yet thorough. Absolute beginners might struggle a bit, but those of any other level of python experience will be fine. Enjoy the online tutorials in the GitHub repo! The exercises in each chapter are easy to understand and tend to build in difficulty. Finish this book, and you'll have a solid understanding of network science and its older cousin graph theory. Demand a sequel!

This is a great book for anyone getting started with network science. There is a bit of light-weight theory in text boxes. The use of the Python NetworkX package gives you a way to try out some of the concepts for yourself.

It's fine. As somebody looking to brush up on network models for doing some data analysis on social networks I thought it was good but it was just a bit cursory. I would really like to see more code examples, problems, and applications in a new edition.

Amazing book, very well written, easy to follow!

I had no prior knowledge of network science before reading this book. Although it is a book meant for beginners, I still felt that it was rather difficult to understand. That issue may lie within me though. The beginning of the textbook is a nice introduction to what network science is. I used the book as part of a course so I have a different perspective than others who just read the book. The Python NetworkX code I used heavily as part of assignments. If you are just reading the book I would still recommend trying the examples from the textbook as you read. The textbook is a solid introduction to network science.

Excellent balance of approachabilty and mathematical detail; suitable to newcomers to the topic. The authors also supply helpful code overviews and a useful repository of Jupyter notebooks to introduce Python libraries for graph analysis.

More for computer science than social science and not much practical application

I have been teaching Network Science to MSc students with limited math and coding skills in a social science department for the last 7 years. The main challenge in doing so was to introduce a suitable textbook to students. I would not give the examples, but there are two type of text books in Network Science 1) the ones that are very much focused on mathematical formalism and analysis of complex networks, and 2) the ones that are focused on the concepts and the story behind those concepts mostly very much focused on social networks. Both groups are fine and serve their own purposes well, however, I needed a book that takes these two, dilutes them down to the entry level, and combines it with hands-on tips and exercises and guidance on how to implement the concepts and methods computationally. Guess what? Finally my dream came true and three great scholars, who have all the authority in the field that is needed to write a reference textbook, released "a first course in network science". This book has everything new learners need to know in order to be able to understand and engage with the fast growing research in network science, and more importantly, to start producing original research on their own. To be perfectly honest in my review, I must add that I was surprised not to see much about multi-layer and multiplex networks, maybe with a dedicated chapter, considering the vast amount of recent literature on them, however, I can also understand that it might be a bit beyond the scope of a "first course". Another positive aspect of the book is that it comes with teaching slides and answer-sheets that can be very attractive to educators. In summary, you need to have a copy of this book whether you are an experience network scientist or just someone who wants to check the water but wants to do so well informed and well prepared.

Excelente escolha para quem busca um primeiro contato com a temática.