Awesome Network Analysis

Type: Curated resource list (awesome list)
Category: Themed directories
Slug: awesome-network-analysis
Source: https://github.com/briatte/awesome-network-analysis

Overview

Awesome Network Analysis is a curated collection of resources for constructing, analyzing, and visualizing network data. It focuses on network science and graph analysis, aggregating tools, libraries, references, and learning materials from across the web.

Features

• Curated Awesome List

  • Follows the general "awesome list" format and standards.
  • Inspired by other notable lists such as Awesome Deep Learning and Awesome Math.
  • Started in 2016 and updated on an irregular basis.

• Network Analysis Focus

  • Emphasizes resources specifically for network and graph analysis.
  • Covers the full workflow: construction, analysis, and visualization of network data.

• Structured Contents

  • Includes a table of contents starting with a Books section.
  • Subsections under Books such as Classics, with further categories implied.

• Resource Types (as indicated by description and structure)

  • Books and reference texts on network science and graph theory.
  • Tools and libraries for network/graph analysis and visualization.
  • Likely includes articles, tutorials, datasets, and code repositories relevant to network analysis (based on being an "awesome" list of resources).

• Searchable for Social Accounts

  • Note that searching for @ on the page returns all listed Twitter accounts.

• Repository Assets

  • README.md as the main curated list.
  • CONTRIBUTING.md for contribution guidelines.
  • check.r and check.log for list maintenance/validation.
  • illustration.png as a visual illustration (e.g., example network image).

• Community Signals (Metadata)

  • Public GitHub repository under the briatte account.
  • ~3.9k stars and ~630 forks (indicating active community interest and reuse).

Intended Use Cases

• Finding learning materials (books and references) on network science.
• Discovering tools and libraries for graph construction, analysis, and visualization.
• Exploring curated links for research, teaching, or applied network analysis projects.

Pricing

• Access to the list is free (public GitHub repository).
• No paid plans or pricing tiers are indicated.