Network Science

The first thing that I noticed was how short this book was for such a topic - compared to Newman's 'Networks' which is about twice as long. This can be explained by the fact that most of the book is devoted to his own models and variations thereof. He overplays his own contributions to the field (which have been debated, refuted, and debunked in some cases) and skims over pretty much everything else. This is a disservice considering the lack of consensus in the field regarding his work - Lior Pachter gives a good overview of the numerous cases of the author's work being questioned or proven wrong - and that he presents the prevalence of the scale-free property as a given when in fact this is empirically and theoretically controversial (he glosses over this by asserting that even if they do not follow a power law distribution, they often exhibit scale free properties).. Overall, the book provides the basics for an understanding of the topic, if you can read past the opinionated presentation, take the BA model with a grain of salt, and skip the lengthy introduction by way of an entire chapter devoted to the author's own achievements. For a comparable price I would recommend Newman's 'Networks' instead, which is more in-depth, broader focused, and objective.

Beautifully produced book. Lots of useful math to build concepts in network science. An enormous amount of time and space is occupied by author (re)writing history to make sure everyone is clear how he made all of his landmark discoveries, after humbly describing his early misfires and the immense ignorance of the field until he made his contributions. The book does not provide nearly enough practical examples to build intuition about applications of networks to various fields of life. Of course you cannot make all happy, but would be great to take this topic to a point where folks can build applied intuition beyond the simple 80:20 rule. Maybe in the next rounds.

Fascinating college-level text which discovers in highly disparate fields a common core of network structures whose connectivity is distributed according to a power law. For anyone who dipped their network science toes in Barabasi's popular book 'Linked', this is going hip deep, with the mathematical underpinnings revealed and plenty of surprising examples from epidemiology, social media, transport systems, communications systems etc. etc. Utterly addictive networking of numerous concepts.

Excellent book and I highly recommend it for network and system engineers to understand basic laws of networks such as small world networks, scale-free network, Achilles hell, resiliency of a network against targeted attack, network failures propagation due to interconnectedness across domains.

great academic and not-academic text

Great introduction to the Science of Networks and complex systems. This was a required text for a university course, however, I found it very readable with an excellent introduction to the history of the field.

Has premier information from network science. An authority in the field, this author has made the principles and methods of network science reader-friendly. I must have book for your professional or personal library. Highly recommended.

If you are working in Connectomics or new AI paradigms, this book is a must. Network Science is the next step in AI.

Great textbook for network analysis!

one of the best references in Network analysis

The first thing that I noticed was how short this book was for such a topic - compared to Newman's 'Networks' which is about twice as long. This can be explained by the fact that most of the book is devoted to his own models and variations thereof. He overplays his own contributions to the field (which have been debated, refuted, and debunked in some cases) and skims over pretty much everything else. This is a disservice considering the lack of consensus in the field regarding his work - Lior Pachter gives a good overview of the numerous cases of the author's work being questioned or proven wrong - and that he presents the prevalence of the scale-free property as a given when in fact this is empirically and theoretically controversial (he glosses over this by asserting that even if they do not follow a power law distribution, they often exhibit scale free properties).. Overall, the book provides the basics for an understanding of the topic, if you can read past the opinionated presentation, take the BA model with a grain of salt, and skip the lengthy introduction by way of an entire chapter devoted to the author's own achievements. For a comparable price I would recommend Newman's 'Networks' instead, which is more in-depth, broader focused, and objective.

Beautifully produced book. Lots of useful math to build concepts in network science. An enormous amount of time and space is occupied by author (re)writing history to make sure everyone is clear how he made all of his landmark discoveries, after humbly describing his early misfires and the immense ignorance of the field until he made his contributions. The book does not provide nearly enough practical examples to build intuition about applications of networks to various fields of life. Of course you cannot make all happy, but would be great to take this topic to a point where folks can build applied intuition beyond the simple 80:20 rule. Maybe in the next rounds.

Fascinating college-level text which discovers in highly disparate fields a common core of network structures whose connectivity is distributed according to a power law. For anyone who dipped their network science toes in Barabasi's popular book 'Linked', this is going hip deep, with the mathematical underpinnings revealed and plenty of surprising examples from epidemiology, social media, transport systems, communications systems etc. etc. Utterly addictive networking of numerous concepts.

Excellent book and I highly recommend it for network and system engineers to understand basic laws of networks such as small world networks, scale-free network, Achilles hell, resiliency of a network against targeted attack, network failures propagation due to interconnectedness across domains.

great academic and not-academic text

Great introduction to the Science of Networks and complex systems. This was a required text for a university course, however, I found it very readable with an excellent introduction to the history of the field.

Has premier information from network science. An authority in the field, this author has made the principles and methods of network science reader-friendly. I must have book for your professional or personal library. Highly recommended.

If you are working in Connectomics or new AI paradigms, this book is a must. Network Science is the next step in AI.

Great textbook for network analysis!

one of the best references in Network analysis

The final frontier in 21st century social science!

I had the chance to use a pre-print of this textbook before it was published, to teach a network science course during the academic year 2015-2016. Its added value in respect to other network science books is that it guides the reader gently, at the right pace and with a lot of insightful examples and visualizations in the world of networks. Students at their first encounter with networks have the chance to absorb increasingly complex network concepts at the right pace. However, intermediate and advanced network scientists do not get bored: they have standard concepts clarified and put under a new light, and they get the chance to expand their knowledge by delving into the Advanced Topics and Appendixes. The textbook is suitable for an interdisciplinary class - indeed in my course I had students from physics, engineering, chemistry, computer science and even marine biology, and all gave positive feedback during the classes, which were closely based on the book materials. All in all, this is a great book both for teachers that plan to teach network science concepts or a whole network science course, or for readers that want to learn network science autonomously.

This is a beautifully set text, with rich color illustrations, figures, and tables that make reading pleasurable and fun. The content is rigorous with an appropriate amount of mathematics for an introductory, graduate-level course in network science. What makes this book stand out from many other textbooks on the subject, is the personal introduction, the historical narrative of the development of the field, and the easy movement back and forth between mathematical concepts and real-world social and scientific applications. From a pedagogical standpoint, the book supports an approach of intuition development and application to the relevant concepts. The text really focuses on the analysis of networks, and doesn't touch on topics like primary or secondary data collection, or computational or software considerations (i.e. no code examples in Python or R) in their analysis. Overall it's an enjoyable read for its clarity and stunning visuals. I look forward to teaching from this text in a future class on applied network science.

The Network Science is a great book, which gives you a totally new perspective about LIFE, including political science, Biology , Physics, Finance etc. Understanding Networks and Big Data will help us to build a better world or at least to understand how the world operates. In the book are practical examples of which include the internet itself, the network of Hollywood actors and films, biological and linguistic networks etc. In the book are also lots of useful mathematics to build original concepts in network science. All in all, this is a great book for everybody who intends to better undestand the world.it is a MUST READ! .

I used this textbook as a student in a network science class. It provided a strong foundation for understanding networks and the analytic techniques associated with them. I particularly appreciated that many of the chapters include "advanced topics" sections - this allows the text to function as a general overview while digging deeply into particularly complex topics. Each chapter ends with a series of suggested homework questions - these are really hard but valuable. Looking back, I learned a lot from working through the problems included in the text and they really helped me understand the material. I'd definitely recommend this text to other network science students or to teachers looking for a good classroom text.

Network Science from Professor Albert-László Barabási is an indispensable read for everyone who aims to understand fundamentals of Network Science. The text and definitions are provided in a didactic way, which helps in reading, especially for those who are having their first contact with network science. This book ranges from basics, like Graph Theory and Graph models to more advanced topics as Communities Structures, Network Robustness, and Spreading Phenomena. All presented concepts are accompanied by beautiful pictures and all the mathematical formalization necessary to derivate insights about networks. At the end of the book, the reader will have a complete view of network science.

Well illustrated with clear language that doesn’t get too mathematical. I really liked it.

Para amantes de las redes, sistemas complejos y teoría de grafo, este libro cumple con tus expectativas. Una vez más Laszlo va llevando al lectorde la mano con el propósito de entender los conceptos básicos de redes hasta ponerlos en práctica. En algunas ocasiones Laszlo como en otras de sus publicaciones e inclusive en su página gusta de presumir sus estudios cayendo en algunas veces hasta la presunción. El libro está precioso, muy bien trabajado, y las imágenes acordé al contenido. En cuanto a la materia existen algunos capítulos que valen la pena que son del 5 al 9, la teoría se enfoca a la práctica y basado en modelos matemáticos ya se comienzan analizar los grados de manera más exhaustiva. El libro lo estoy utilizando para mi trabajo de análisis de patrones en redes sociales con NLP y Deep Learning

Fiquei surpreso com a qualidade da edição, o livro atende ao que se propõe, um curso básico de redes complexas, com muito material extra para completar.