Awesome Network Analysis

An awesome list of resources to construct, analyze and visualize network data.

Table of Contents

• Books
  • Overviews
  • Language-specific
  • Method-specific
  • Topic-specific
• Courses
• Datasets
• Journals
• Professional groups
• Review Articles
• Software
  • JavaScript
  • Python
  • R
• Tutorials
• Varia
• Contribution Guidelines

Books

Overviews

1. Networks. An Introduction, by Mark E.J. Newman (2010).

• Networks, Crowds, and Markets: Reasoning About a Highly Connected World, by David Easley and Jon Kleinberg; complete pre-publication draft online (2010).
• Réseaux sociaux et structures relationnelles, by Emmanuel Lazega, in French (2014).
• Sociologie des réseaux sociaux, by Pierre Mercklé, in French (2011).
• Social Network Analysis. Methods and Applications, by Stanley Wasserman and Katherine Faust (1994).

Method-specific

1. Exponential Random Graph Models for Social Networks, by Dean Lusher, Johan Koskinen and Garry Robins (2013).

• Multilevel Network Analysis for the Social Sciences, by Emmanuel Lazega and Tom A.B. Snijders (2016).
• Political Networks. The Structural Perspective, by David Knoke (1994).

Software-specific

1. Analyzing Social Networks (using UCINET), by Stephen P. Borgatti, Martin G. Everett and Jeffrey C. Johnson (2013).

• Network Analysis with R/igraph, by Gabor Csárdi, Thomas Nepusz and Eduardo M. Airoldi (in preparation).
• Network Analysis with Python/igraph, by Thomas Nepusz, Gabor Csárdi and Eduardo M. Airoldi (in preparation).
• Statistical Analysis of Network Data with R, by Eric D. Kolaczyk and Gabor Csárdi (2014).

Topic-specific

1. Neighbor Networks. Competitive Advantage Local and Personal, by Ronald S. Burt (2010).

• Comparing Policy Networks. Labor Politics in the U.S., Germany, and Japan, by David Knoke et al. (1996).

Courses

1. Complex Networks, by Peter Sheridan Dodds (2016).

Datasets

1. Gephi Datasets.

• KONECT - The Koblenz Network Collection.
• Mark E.J. Newman's Network Data.
• Pajek Datasets
• Siena Datasets.
• Stanford Large Network Dataset Collection.
• tnet Datasets.
• UCI Network Data Repository.

Journals

1. Applied Network Science (Springer Open).

• Computational and Mathematical Organization Theory (Springer).
• Computational Social Networks (Springer Open).
• Connections (INSNA).
• Journal of Complex Networks (Oxford).
• The Journal of Mathematical Sociology (Taylor & Francis).
• Journal of Social Structure (INSNA).
• Network Science (Cambridge).
• REDES, in Spanish (INSNA).
• Social Network Analysis and Mining (Springer).
• Social Networks (Elsevier).

Professional groups

1. AFS RT 26 “Réseaux sociaux” - Thematic Network of the French Sociological Association, in French.

• ECPR Political Networks SG - Standing Group of the European Consortium for Political Research (Twitter account).
• GDR Analyse de réseaux en sciences humaines et sociales, in French.
• Groupe FMR - Flux, Matrices, Réseaux, in French.
• INSNA: International Network for Social Network Analysis (mailing-list).
• NetSci: Network Science Society.
• APSA Political Networks - Organized Section of the American Political Science Association.

Review Articles

1. "Network Analysis and Political Science" (Annual Review of Political Science, 2011).

• "Statistical Models for Social Networks" (Annual Review of Sociology, 2011).

Software

1. Cytoscape - Cross-platform Java program to build, analyze and visualize networks.

• Discourse Network Analyzer (DNA) - Qualitative content analysis tool with network export facilities, written in Java with R integration.
• Gephi - Cross-platform, free and open source tool for network visualization.
• GraphViz - Software to draw graphs in the DOT language.
• Neo4j - Open source, scalable graph database, used by companies like Linkurious.
• networks.tb - A suite designed for analyzing socio-semantic networks, written in C.
• NodeXL - Free, open-source template for Microsoft Excel to explore network graphs.
• ORA-LITE - Windows program for dynamic meta-network assessment and analysis.
• Pajek - Windows program for large network analysis, free for noncommercial use.
• PNet - Simulation and estimation of exponential random graph models (ERGMs), written in Java for Windows.
• Siena - Simulation Investigation for Empirical Network Analysis, formerly a Windows program, now an R package.
• Stanford Network Analysis Project - C++ general purpose network analysis and graph mining library; available as a Python library and through NodeXL.
• UCINET - Windows commercial software package for the analysis of social network data.
• Visone - Cross-platform Java network analysis and visualization program, free for noncommercial use.
• VOSviewer - Cross-platform software tool for constructing and visualizing bibliometric networks, written in Java.

JavaScript

For more awesome Python packages, see the Awesome JavaScript list.

• d3.js - JavaScript visualization library that can plot force-directed graphs.
• jLouvain - Louvain community detection for Javascript (example).
• Sigma - JavaScript library dedicated to graph drawing.
• vis.js - JavaScript library with network visualization capabilities.

Python

Most items below are from a Google spreadsheet by Michał Bojanowski and others.
For more awesome Python packages, see the Awesome Python list.

1. graphviz - Python renderer for the DOT graph drawing language.

• linkpred - Assess the likelihood of potential links in a future snapshot of a network.
• networkx - Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
• python-igraph - Python version of the igraph network analysis package.

R

See also this Google spreadsheet by Ian McCulloh and others.
For more awesome R packages, see the Awesome R list.

• Bergm - Tools to analyse Bayesian exponential random graph models.
• CCAS - A statistical model for communication networks.
• concoR - A translation of the CONCOR network blockmodeling algorithm (blog post).
• ergm - Estimation of Exponential Random Graph Models.
• GERGM - Estimation and diagnosis of the convergence of Generalized Exponential Random Graph Models (GERGM).
• geomnet - A single-geometry approach to network visualization with ggplot2.
• ggnetwork - A multiple-geometries approach to plot network objects with ggplot2.
• ggraph - A grammar of graph graphics built in the spirit of ggplot2.
• hergm - Estimate and simulate hierarchical exponential-family random graph models with local dependence.
• igraph - A collection of network analysis tools.
• latentnet - Latent position and cluster models for network objects.
• networkD3 - D3 JavaScript network graphs from R.
• ndtv - Tools to construct animated visualizations of dynamic network data in various formats.
• network - Basic tools to manipulate relational data in R.
• networkDynamic - Support for dynamic, (inter)temporal networks.
• rgexf - Export network objects from R to GEXF, for manipulation with network software like Gephi or Sigma.
• RSiena - Simulation Investigation for Empirical Network Analysis; fits models to longitudinal network data.
• sna - Basic network measures and visualization tools.
• spnet - Methods for dealing with spatial social networks.
• statnet - The project behind many R network analysis packages.
• tnet - Network measures for weighted, two-mode and longitudinal networks.
• tsna - Tools for temporal social network analysis.
• visNetwork - Using vis.js library for network visualization.
• xergm - Extensions of Exponential Random Graph Models.

Tutorials

1. Analyse des réseaux : une introduction à Pajek, in French (2011).

• Basic and Advanced Network Visualization with Gephi and R (Sunbelt 2016).
• Exponential Random Graph Models (ERGMs) Using statnet (Sunbelt 2015).
• Guides for Using the statnet Package (2010).
• Implementing an ERGM From Scratch in Python (2014).
• L'analyse des graphes bipartis, in French (2013).
• La détection de communautés avec Pajek 3.6, in French (2012).
• Modeling Valued Networks with statnet (Sunbelt 2013).
• Network Analysis and Visualization with R and igraph (NetSciX 2016).
• Practical Social Network Analysis With Gephi (2014).
• Static and Dynamic Network Visualization with R (PolNet 2015).
• Working with Bipartite/Affiliation Network Data in R (2012).

Varia

• Blog posts about networks by Pierre Mercklé, in French.
• Network Fact - A Twitter account about networks, graph theory, and related topics.
• Videos from the Political Networks 2009 conference.

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Contribution Guidelines

Please contribute to this list by sending a pull request after reading the Contribution Guidelines for stylistic indications.

• All sources are organized alphabetically with date and language mentions when relevant.
• Authors are mentioned for books and courses only.
• To cite R packages, please cite the stable CRAN version when it exists.
• To cite Python packages, please cite the PyPi version when it exists.

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License

To the extent possible under law, the authors of this list (François Briatte, Ian McCulloh) have waived all copyright and related or neighboring rights to this work.