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Best resources to learnNetwork Science

Study sheet

Network science studies the structure of connections in society, biology and technology. You will learn graph measures, small-world and scale-free networks, spreading processes and community detection.

5 resources · · How we curate

🎓Courses(1)

course

Social and Economic Networks: Models and Analysis

This is the only elite-institution video course that treats networks from the social science side. Stanford course taught by Matthew O. Jackson in eight modules: network definitions and measures, random network models, strategic network formation, diffusion, learning on networks and games on networks. The course is free to audit, and a certificate costs extra.

advanced🇬🇧

📚Books(2)

book

Networks, Crowds, and Markets: Reasoning about a Highly Connected World

Cornell textbook by David Easley and Jon Kleinberg on social and economic networks: strong and weak ties, homophily, structural balance, link analysis, power laws, information cascades and network effects. It covers the sociology side (ties, balance, homophily, cascades) that Barabási's physics-oriented book treats lightly, and it needs little math. The authors host a complete free pre-publication draft.

beginner🇬🇧
bookPaid

Networks (2nd Edition)

Comprehensive graduate textbook on network science covering how network data are gathered, centrality and structural measures, algorithms for large networks, random graph and configuration models, community detection, percolation and robustness, and epidemic and dynamical processes, with the underlying mathematics derived in full.

intermediate🇬🇧

🌐Websites(2)

website

NetworkX Tutorial

Official tutorial for NetworkX, the standard Python library for network analysis. It covers building graphs, node and edge attributes, directed graphs and multigraphs, random graph generators, degree, shortest paths and clustering analysis, and drawing with Matplotlib. This is the practical step from theory to computing graph measures on real data.

beginner🇬🇧
website

Network Science (full online edition)

Interactive textbook, free from the author, whose chapters build the random network model and then break it: degree distributions, scale-free networks, the small-world property, robustness and percolation, each checked against real biological, social and technological network data.

intermediate🇬🇧
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Frequently Asked Questions

What are the best free resources to learn Network Science?

Dantes has curated 5 resources for Network Science, including 2 books, 1 courses, 2 websites. All resources are hand-picked for quality — no algorithmic filler. Browse the full list above to find the format that works best for you.

Is Network Science hard to learn?

Network Science is approachable at the beginner level — there are resources here specifically for those starting from scratch. As you progress, intermediate and advanced material is also available to take your skills further.

What types of Network Science learning resources are available on Dantes?

For Network Science, Dantes has curated 2 books, 1 courses, 2 websites. Each resource type serves a different learning style: videos and YouTube for visual learners, books for depth, courses for structured progression, and websites for quick reference.

How does Dantes select Network Science resources?

Dantes is an algorithm-free learning directory. Resources are hand-curated based on quality, accuracy, and usefulness — not engagement metrics or paid placements. The goal is to surface the best learning material for Network Science, whether it's a free YouTube series, a classic textbook, or an open courseware from a top university.

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