---
product_id: 210077540
title: "A First Course in Network Science"
price: "NT$3756"
currency: TWD
in_stock: true
reviews_count: 10
url: https://www.desertcart.tw/products/210077540-a-first-course-in-network-science
store_origin: TW
region: Taiwan
---

# A First Course in Network Science

**Price:** NT$3756
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- **What is this?** A First Course in Network Science
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Review: Great textbook for fundamental network science concepts. Highly recommended! - 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.
Review: Amazing Content and Delivery - 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!

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #462,486 in Books ( See Top 100 in Books ) #47 in System Theory #161 in Mathematical Physics (Books) #212 in Physics (Books) |
| Customer Reviews | 4.5 4.5 out of 5 stars (91) |
| Dimensions  | 7.5 x 0.75 x 9.75 inches |
| Edition  | 1st |
| ISBN-10  | 1108471137 |
| ISBN-13  | 978-1108471138 |
| Item Weight  | 1.7 pounds |
| Language  | English |
| Print length  | 300 pages |
| Publication date  | January 30, 2020 |
| Publisher  | Cambridge University Press |

## Images

![A First Course in Network Science - Image 1](https://m.media-amazon.com/images/I/81zbm4uwLwL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Great textbook for fundamental network science concepts. Highly recommended!
*by A***A on January 16, 2023*

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.

### ⭐⭐⭐⭐⭐ Amazing Content and Delivery
*by D***C on April 9, 2022*

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!

### ⭐⭐⭐⭐⭐ The title is accurate!
*by S***N on April 22, 2021*

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.

## Frequently Bought Together

- A First Course in Network Science
- Network Science
- Networks

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*Last updated: 2026-04-25*