---
title: Network Science
description: 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.
category: social-sciences
subcategory: sociology
difficulty: beginner, intermediate, advanced
url: /subject/network-science
---

# Network Science

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.

## Available Resources

2 Books • 1 Courses • 2 Websites

## Websites

### 1. NetworkX Tutorial

**Author:** NetworkX Developers

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.

**Difficulty:** Beginner | **Language:** English | **Price:** Free

**Link:** https://networkx.org/documentation/stable/tutorial.html

**Tags:** networkx, python, network-analysis, graph-algorithms

### 2. Network Science (full online edition)

**Author:** Albert-László Barabási, Márton Pósfai

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.

**Difficulty:** Intermediate | **Language:** English | **Price:** Free

**Link:** https://networksciencebook.com/

**Tags:** network-science, scale-free-networks, random-networks, small-world-networks, network-robustness

## Courses

### 1. Social and Economic Networks: Models and Analysis

**Author:** Matthew O. Jackson

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.

**Difficulty:** Advanced | **Language:** English | **Price:** Free

**Link:** https://www.coursera.org/learn/social-economic-networks

**Tags:** social-networks, network-economics, network-formation, diffusion, game-theory

## Books

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

**Author:** David Easley, Jon Kleinberg

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.

**Difficulty:** Beginner | **Language:** English | **Price:** Free

**Link:** https://www.cs.cornell.edu/home/kleinber/networks-book/

**Tags:** network-science, social-networks, game-theory, information-cascades, link-analysis

### 2. Networks (2nd Edition)

**Author:** Mark Newman

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.

**Difficulty:** Intermediate | **Language:** English | **Price:** Paid

**Link:** https://www.amazon.com/dp/0198805098?tag=edmonddante07-20

**Tags:** network-science, random-graphs, percolation, epidemic-modeling, configuration-model

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