Your first time on this page? Allow me to give some explanations.
Awesome Network Analysis
A curated list of awesome network analysis resources.
Here you can see meta information about this topic like the time we last updated this page, the original creator of the awesome list and a link to the original GitHub repository.
Thank you briatte & contributors
View Topic on GitHub:
Search for resources by name or description.
Simply type in what you are looking for and the results will be filtered on the fly.
Further filter the resources on this page by type (repository/other resource), number of stars on GitHub and time of last commit in months.
_, by Samuel F. Sampson (unpublished PhD dissertation, 1968).
_, by Stanley Wasserman and Katherine Faust (1994).
_, by Nicholas A. Christakis and James H. Fowler (2009).
_, by Albert-László Barabási (2002).
_, by the NetSciEd team (c. 2016) - Available in several languages (paper).
_, by Mark Buchanan (2003).
_, edited by George A. Barnett - Covers all sorts of network-related themes (many of them not formal) as well as social network analysis (2011).
_, edited by Reda Alhajj and Jon Rokne (2014).
_, by Albert-László Barabási - Full book online (2016).
_, by the U.S. National Research Council - Full book online (2005).
_, by Ted G. Lewis (2011).
_, by Mark E.J. Newman (2010).
_, by David Easley and Jon Kleinberg - Full pre-publication draft (review; 2010).
_, by Emmanuel Lazega, in French (2014).
_, edited by John Scott and Peter J. Carrington (2011).
_, by Pierre Mercklé, in French (2011).
_, by Matthew O. Jackson (2008).
_, by Ian McCulloh, Helen Armstrong and Anthony Johnson (2013).
_, by Jeroen Bruggeman (related material; 2008).
, by Marina Hennig _et al. (2013).
_, by Charles Kadushin (2012).
_, by John Harris, Jeffry L. Hirst and Michael Mossinghoff (2008).
_, by Arthur Benjamin, Gary Chartrand and Ping Zhang (2015).
_, by John A. Bondy and Uppaluri S.R. Murty (2008).
_, by Reinhard Diestel - Full book online, also in Chinese and German (2016).
_, by Frank Harary - Full book online (1969).
_, by Gary Chartrand, Linda Lesniak and Ping Zhang (2016).
_, by Daniel Guichard - Full book online (2016).
_, by Radhakrishnan Nagarajan, Marco Scutari and Sophie Lèbre (website; 2013).
_, by Marco Scutari and Jean-Baptiste Denis (website; 2014).
_, by Manuel Lima - Hundreds of beautiful tree diagrams, from all periods of history (2014).
_, edited by Dean Lusher, Johan Koskinen and Garry Robins (2013).
_, by Patrick Doreian, Vladimir Batagelj and Anuška Ferligoj (2004).
_, edited by Roberto Tamassia (chapter proofs; 2013).
, edited by Marten Düring _et al., in German (2016).
_, by Jenine K. Harris (2014).
_, edited by Markus Gamper and Linda Reschke, in German (2010).
_, edited by Markus Gamper, Linda Reschke and Michael Schönhuth, in German (2012).
_, edited by Emmanuel Lazega and Tom A.B. Snijders (2016).
_, edited by Andreas Kerren, Helen C. Purchase and Matthew O. Ward (2014).
_, edited by Carl Knappett (2013; review in French).
_, edited by Ulrik Brandes and Thomas Erlebach - Covers network centrality, clustering, blockmodels, spatial networks and more (2005).
_, by David Knoke (1994).
, by Nick Crossley _et al. (2015).
, by Vladimir Batagelj _et al. (2014).
_, by David Joyner, Minh Van Nguyen, and David Phillips - Full book online (2013).
_ (using UCINET), by Stephen P. Borgatti, Martin G. Everett and Jeffrey C. Johnson (2013).
_, by Douglas A. Luke (2015).
_, by Guido Caldarelli and Alessandro Chessa (2016).
_ (covering many programs), edited by Michael Jünger and Petra Mutzel (2004).
_ (using mostly UCINET), by Robert A. Hanneman and Mark Riddle - Full book online (2001).
_, by Ken Cherven (2015).
_, by Ken Cherven (2013).
_ (using Python), by Maksim Tsvetovat and Alexander Kouznetsov (code; 2011).
_, by Katherine Giuffre (2013).
, by David Knoke _et al. (1996).
_ edited by Tom Brughmans, Anna Collar and Fiona Coward (2016; companion website).
_, by Linton C. Freeman, in English and several other languages (2004; follow-up paper, 2011).
_, by Laura Bringmann (2016; PhD dissertation).
_, by Alain Barrat, Marc Barthélemy and Alessandro Vespignani (2008).
_, by Alex Fornito, Andrew Zalesky and Edward Bullmore (2016).
_, by Ronald S. Burt (2010).
_, by Katharina A. Zweig (2016).
_, edited by Balázs Vedres and Marco Scotti (2012).
_, edited by Yann Bramoullé, Andrea Galeotti and Brian Rogers (2016).
_, by Philip Leifeld (2016).
_, by Duncan J. Watts (2003).
_, by Peter Monge and Nosh Contractor (2003).
_, by Anne-Marie Slaughter (2017); applies network science to world politics.
_, by Nick Crossley (2011).
_, by Lothar Krempel, in German.
Convened by the Cambridge Networks Network.
Organized by the APSA Organized Section on Political Networks (PolNet).
Organized by the Network Science Society (NetSci).
Talk by Dan Larremore at NetSci 2019.
Organized by the International Network for Social Network Analysis (INSNA).
by Peter Sheridan Dodds (University of Vermont, 2016; Twitter: @networksvox).
by Paul Van Dooren - Full lecture slides (Hamilton Institute, Dublin, 2009).
by Aaron Clauset - Full lecture slides and readings (University of Colorado, 2014).
by Cesar Hidalgo (MIT, 2011).
by David Easley, Jon Kleinberg and Eva Tardos (presentation; Cornell University via edX, 2016).
by Mardavij Roozbehani and Evan Sadler (MIT, 2018).
by Daron Acemoglu and Asu Ozdaglar (MIT, 2009).
by Constantine Dovrolis - Mostly open access readings (Georgia Tech, 2015).
by Albert-László Barabási, Sean Cornelius and Roberta Sinatra (Northeastern University, 2015).
by Zeev Maoz (University of California in Davis, 2012).
by Matthew O. Jackson (Stanford University via Coursera, 2015).
by Lada Adamic (University of Michigan via Coursera, not yet run).
and Intermediate Social Network Theory, by Matthew J. Denny - Workshop notes and slides (2014–5).
by Andrej Mrvar (University of Ljubljana, 2016).
by Dennis M. Feehan (University of Berkeley, 2017).
Bill cosponsorship networks in European parliaments.
Gephi - The Open Graph Viz Platform
Large collection of networks described and indexed by Aaron Clauset’s research group.
Historical data on the international connections between 45 currencies.
Includes, among other things, networks of collaboration in DBpedia and Wikipedia, GitHub (companion handbook).
Over 300 datasets of all sorts, in UCINET format.
Fully searchable database containing hundreds of real-world networks.
Network data sets from Albert-László Barabási’s Network Science book. Includes data on IMDB actors, arXiv scientific collaboration, network of routers, the US power grid, protein-protein interactions, cell phone users, citation networks, metabolic reactions, e-mail networks, and nd.edu Web pages.
Two-mode and one-mode data on gender representation in Norwegian firms.
Network data obtained through the SocioPatterns sensing platform.
_, in English and in French (GDR ARSHS).
_ (Springer, gated).
_ (Taylor & Francis, gated).
_ (INSNA). Older archives.
_, in English and in French (Revues.org).
_, in Spanish (INSNA).
Thematic Network of the French Sociological Association (AFS), in French (old website).
Organized Section of the American Political Science Association (APSA). Twitter: @PolNetworks.
Standing Group of the European Consortium for Political Research. Twitter: @politicalnets.
in French - Research group based in Paris.
Organized by the Network Science Society (NetSci).
Research Groups (USA)
Research group studying social networks at the University of Southern California.
Research group based at the University of Southern California School of Medicine.
Research division within the Department of Medicine at Brigham and Women’s Hospital.
Reading list from a seminar held at MIT in 2001–2.
Led by Bruce A. Desmarais at Penn State University.
NISS Lab) - Led by Skyler J. Cranmer at Ohio State University.
Features an NSF-funded graduate programme.
Headed by Carter T. Butts. Part of the Center for Networks and Relational Analysis (CNRA) at the University of California in Irvine.
Features a PhD in Network Science program.
Led by Albert-László Barabási.
Led by Alessandro Vespignani.
Non-profit study group of ecological networks (“food webs”).
Research Groups (Other)
Research network on complex networks.
Focused on economic/organisational network analysis.
Features a PhD in Network Science program.
Wroclaw-based research group that studies, among many things, complex networks and other network-related topics.
Interdisciplinary group of researchers at the Marc Bloch Centre in Berlin, with many network science projects.
French research group with funds to support training and workshops on network analysis for social scientists.
Platform for scholars interested in network analysis for historical research.
Russian group based at the National Research University in Moscow.
Research group at the Catholic University of Louvain (official page).
Currently studies covert networks.
Tokyo-based research group, studying bi-, tri- and k-partite (hyper)networks.
Research network at the University of Toronto, led by Barry Wellman.
Historical research project on the connections between Jewish intellectuals.
A research program on networks and regulation.
Seminar based at Sciences Po in Paris, France.
in Spanish - Information network based at the Universitat Autònoma de Barcelona.
in French - Blog posts from a research group on historical networks.
Interdisciplinary research group that uses wireless sensors to study social network data.
Research platform based at the Austrian Academy of Sciences that focuses on applying network theory and visualisation to medieval history.
Research and software development project located at the Australian National University.
Archeological and Historical Networks
in French (Revue d’histoire moderne et contemporaine, 2005).
in French (Les Nouvelles de l’Archéologie, 2014).
Programming Historian, 2015).
preprint](http://arxiv.org/abs/q-bio/0604006); IET Systems Biology, 2007).
in French (Geschichte und Informatik, 2015).
in The Historian’s Macroscope, 2013).
Annual Review of Anthropology, 2014).
in German (Prozesse. Formen, Dynamiken, Erklärungen, 2015).
Archaeological Review from Cambridge, 2014).
Journal of Archaeological Method and Theory, 2013).
Bibliographic, Citation and Semantic Networks
Journal of Informetrics, 2012).
Models of Science Dynamics, 2012).
Digital Humanities Quarterly, forthcoming).
preprint](http://camille.roth.free.fr/travaux/roth--sociosemantic-systems-acs-proofs.pdf); Advances in Complex Systems, 2013).
Annual Review of Sociology, 2015).
Biological, Ecological and Disease Networks
Handbook of Graph Drawing and Visualization, 2014).
Annual Review of Clinical Psychology, 2013).
Accessible introduction to (cellular) network analysis (Nature Reviews Genetics, 2004).
Nature Review Genetics, 2011).
Social Networks, 1985).
Also includes an impressive list of network analysis software (Pharmacology & Therapeutics, 2013).
Complex and Multilayer Networks
From network theory to complexity theory (IEEE Control Systems Magazine, 2007).
special issue of Science, 2009).
Annual Review of Condensed Matter Physics, 2019).
Reviews of Modern Physics, 2002).
Ethics of Network Analysis
preprint][conway2014]; British Journal of Management, 2014).
special issue of Social Networks, 2005).
The Journal of Applied Behavioral Science, 2003).
Statistics Surveys, 2017).
preprint](http://www.stats.ox.ac.uk/~snijders/SnijdersSteglichVdBunt2009.pdf); Social Networks, 2010).
preprint](http://patrickdoreian.com/NEW/wp-content/papers_resources/chapters/Positional_Analysis_and_Blockmodeling.pdf); -->Computational Complexity, 2012).
Mathematics & Social Sciences, 1997).
Annual Review of Sociology, 2011).
Book-length review (preprint; Foundations and Trends in Machine Learning, 2010).
Journal of Theoretical Politics, 1999).
Models and Methods in Social Network Analysis, 2005).
Encyclopedia of Complexity and Systems Science, 2009; poster version).
Social, Economic and Political Networks
Mathématiques et sciences humaines, 2011).
Annual Review of Sociology, 2001).
ESRC NCRM Discussion Paper, 2010).
Annual Review of Political Science, 2011).
International Organization, 2009).
preprint](http://patrickdoreian.com/NEW/wp-content/papers_resources/new_papers_4-13/Networks_in_Socia_Psychology_Lewin.docx); -->Encyclopedia of Social Network Analysis and Mining, 2014).
Journal of Economic Perspectives, 2014).
preprint](http://patrickdoreian.com/NEW/wp-content/papers_resources/new_papers_4-13/positions_and_roles.pdf); -->The SAGE Handbook of Social Network Analysis, 2011).
PSC Working Paper Series, 2013).
preprint](http://opensiuc.lib.siu.edu/cgi/viewcontent.cgi?article=1048&context=pn_wp); PS: Political Science and Politics, 2011).
Annual Review of Criminology, 2019).
by Pascal Cristofoli, in French - Reviews the current state of relational sociology and network analysis in light of the large-scale and online data (Réseaux, 2008).
by Steven M. Goodreau, James A. Kitts and Martina Morris - Accessible introduction to the logic and application of exponential random graph modeling (Demography, 2001).
by Peter S. Bearman, James Moody and Katherine Stovel - Classic example of topological network analysis applied to a network of affective and sexual ties (American Journal of Sociology, 2004).
by Travis Martin et al. - Highly typical study of scientific publishing productivity and collaboration through temporal network analysis (preprint; Physical Review E, 2013).
by Jon Kleinberg - Discusses small-world effects and social contagion within the context of the Internet and social media (Communications of the ACM, 2008).
by Michael Eve (English version; Réseaux, 2002).
by Cosma R. Shalizi and Andrew C. Thomas - Makes a very important point for the analysis of network diffusion and influence (Sociological Methods and Research, 2011).
by Alain Barrat, in French - Accessible introduction to the study of complex networks (Communication & Organisation, 2013).
by Mustafa Emirbayer and Jeff Goodwin (American Journal of Sociology, 1994), and Manifesto for a Relational Sociology, by Mustafa Emirbayer (American Journal of Sociology, 1997) - Sociological foundations for a science of social ties.
by Franco Moretti - Example applications of (fictional) network analysis in literary studies (New Left Review, 2011).
by Tore Opsahl, Filip Agneessens and John Skvoretz - Explores the generalization of network centrality and distance measures to (positively) valued graphs (Social Networks, 2010; companion website).
by Albert-László Barabási and Eric Bonabeau - Early, accessible formulation of the “networks are everywhere” argument (Scientific American, 2003).
by Tyler J. VanderWeele and Weihua An - Reviews the different ways in which network analysis can produce meaningful causal statements, as well as the inherent limits of network analysis for doing so (Handbook of Causal Analysis for Social Research, 2013).
by Kieran Healy - Network analysis meets science studies: social networks, like financial markets, are highly subject to performativity, i.e. the possibility that reality might be altered by its theoretical inquiry (European Journal of Sociology, 2015).
by Carter T. Butts - On choosing the right network representation to frame a research problem.
by John F. Padgett and Christopher K. Ansell - Classic analysis of power relations in the Renaissance Florentine state (American Journal of Sociology, 1993).
by Mark Granovetter - Arch-classic example of applying network analysis to a social issue: jobseeking (American Journal of Sociology, 1973).
The Journal of Economic History, 2005) and The Empirics of International Currencies: Network Externalities, History and Persistence (The Economic Journal, 2009), both by Marc Flandreau and Clemens Jobst - Network analysis of the foreign exchange system in the late 19th century (data).
by A. James O’Malley and Jukka-Pekka Onnela - 50-page introduction to network analysis, with just the right amount of detail on all aspects of it (The Handbook of Health Services Research, forthcoming 2017).
Graph Theory library for Ruby
IGraph/M is the igraph interface for Mathematica
Network-based spatial analysis software for solving complex routing problems.
Cross-platform Java program to identify clusters and communities through the Clique Percolation Method (CPM).
Cross-platform program to produce circular layouts of network data, written in Perl.
Illustrated through an archaeological and geographical case study (2013).
Qualitative content analysis tool with network export facilities, written in Java with R integration.
Cross-platform Java program for ego network analysis.
Server-side software for social network data collection and processing.
Online tool aimed at representing and sharing gene interaction networks as well as Petri net models.
in German (2016).
Cross-platform tool intended for the prediction of human epidemics.
Collaborative platform for mapping, analyzing and publishing data-networks.
Cross-platform software to draw graphs in the DOT graph drawing language.
Apache Spark's API for graphs and graph-parallel computation.
Cross-platform, free and open source tool to study multilayer networks, based on R and GNU Octave.
Set of tools to collect personal network data (in early development).
Web-based tool to compute Strona and Veech’s node overlap and segregation measures.
Web-based data management, network analysis and visualisation environment (blog).
Free, open-source template to explore network graphs with Microsoft Excel.
Series of blog posts on using NodeXL (2013).
Windows program for dynamic meta-network assessment and analysis.
Web-based platform to analyze social media data, including through Twitter-based and co-occurrence networks.
Windows program for large network analysis, free for noncommercial use.
Web-based spatial network visualization tool by the Humanities + Design research lab at Stanford University.
Excel-based tool for building networks from surveys.
Windows program and C++ library to analyze planar graphs.
Simulation and estimation of (one-mode and multilevel) exponential random graph models (ERGMs), written in Java for Windows.
Web-based platform to both analyze network data as well as collect network data via relationship-based surveys.
Cross-platform Java program for genealogical network analysis.
Set of tools intended for the analysis of complex networks, built on top of Radalib, a library written in Ada.
Simulation Investigation for Empirical Network Analysis. Formerly a Windows program, now developed as the RSiena R package.
Cross-platform program that includes a simple Web crawler to construct hyperlink networks.
Cross-platform tool to perform large-scale, distributed network computations with Apache Spark’s GraphX module; written in Java and Scala.
Cross-platform program for the visualization and exploration of complex networks.
Several Windows programs developed by the same team as Siena.
Cross-platform network analysis and visualization framework built on top of a C++ library, with plugins dedicated to specific biological and physical networks. Also available through its Python package.
Windows commercial software package for the analysis of social network data.
Software suite for online (hyperlink) network analysis, by the VOSON research project.
Web-based software for the collection and analysis of online network data.
quick tutorial](https://blogs.k-state.edu/it-news/2013/04/09/the-nodexl-series-using-voson-for-hyperlink-network-analysis-part-9/); to be discontinued in 2016).
Cross-platform program to download and visualize Usenet data. Developed for a Masters degree.
Cross-platform Java program for ego network analysis.
also available in Spanish; 2011).
Cross-platform Java network analysis and visualization program, free for noncommercial use.
Illustrated through an archaeological case study (2015).
Cross-platform Java program to visualize online social networks.
Basic graph theory algorithms
Programs to identify link communities in complex networks
Algorithms for finding weighted modularity in bipartite networks
Algorithms to detect overlapping communities in networks, written in Java.
Force-directed layout included in Gephi (paper).
Community detection method, available in C++ and R.
MATLAB and Python implementations of a Bayesian community detection algorithm.
C / C++
C++ code to generate weighted and unweighted graphs.
C++ library that provides a generic interface to access graph structures.
C++ code for the Infomap method of multilevel community detection.
C++ code for the Louvain multi-level community detection algorithm.
C program designed for analyzing socio-semantic networks. Runs on Linux and Mac OS X.
Self-contained C++ class library for diagram, network and tree layouts.
C++ algorithm, also available as a Gephi plugin.
C++ general purpose network analysis and graph mining library. Available as a Python library and in Microsoft Excel via NodeXL.
Simple prototype for creating derived graphs from social network data using Deriggy and Fluo
Force-directed graph layout using velocity Verlet integration.
A D3 force plug-in for programmatically determining a set of vectors' angles and magnitudes
Interactive open source visualization platform for multivariate dynamic networks.
Allows the user to manipulate documents based on data to render charts in SVG.
Visualization library to build and manipulate graphs through a simple API. Powered by d3.js and WebCola.
Library based on d3.js that provides a graph based search interface.
Bayesian Networks for Julia
A Julia wrapper for the Smile C++ Structural Modeling, Inference, and Learning Engine for Bayesian & Influence Networks
Everything you've never dreamed about measuring on ecological networks.
Studying networks that evolve over time.
Working with graphs in Julia
An optimized graphs package for the Julia programming language
Additional functionality for LightGraphs.jl
Layout algorithms for graphs and trees in pure Julia.
(DEPRECATED) Additional graph flexibility for LightGraphs
(DEPRECATED) Centrality measures for Graphs.jl
Graph and Network algorithms in Julia
Network Flows structures and algortihms for Julia v0.4+
Julia Interface to visualize Graphs.
A Julia package for statistical inference, data manipulation and visualization of phylogenetic networks
This library generates graph layouts using the TikZ graph layout package.
Toolbox for complex-network analysis of structural and functional brain-connectivity data, with links to many related projects.
Random network toolbox that implements nine network models.
Variant of the Louvain community detection algorithm.
Interactive network visualization in Python and Dash, powered by Cytoscape.js
Python package for graph statistics
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Easy link prediction tool
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Visualization Package for NetworkX
PyGraphistry is a library to extract, transform, and visually explore big graphs
Python module for network manipulation and analysis, written mostly in C++ for speed.
Python utility for drawing networks as hive plots on matplotlib, a more comprehensive network visualization.
Python package to turn bibliometrics data into authorship and citation networks.
Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
using networkx and numpy (2014).
A solid implementation of Louvain community detection algorithm.
A Python interface for SNAP (a general purpose, high performance system for analysis and manipulation of large networks).
Python 3 library for temporal network analysis.
A Statistical Model for Communication Networks
CONCOR for R
An R package which implements an extension to the TPME model of Krafft et al. (2012)
Graph and network visualization using tabular data in R.
R package to analyze two-mode networks
A Modern and Flexible Neo4J Driver
R package containing several network datasets
R package: networkdiffusion
R package for signed networks
R package, using vis.js library for network visualization
Additive and multiplicative effects models for relational data.
Provides methods for binarizing a weighted network retaining only significant edges.
Tools to analyse Bayesian exponential random graph models (BERGM).
Functions to visualize bipartite (two-mode) networks and compute indices commonly used in ecological research. See also:
levelnet R package.
Implementats generalized blockmodeling for valued networks.
Tools for performing graph theory analysis of brain MRI data.
Tools to fit temporal ERGMs by bootstrapped pseudolikelihood. Also provides MCMC maximum likelihood estimation, goodness of fit for ERGMs, TERGMs, and stochastic actor-oriented models (SAOMs), and tools for the micro-level interpretation of ERGMs and TERGMs.
Computes distances on dual-weighted directed graphs, such as street networks, using priority-queue shortest paths.
Estimation and diagnosis of the convergence of Generalized Exponential Random Graph Models (GERGM).
Single-geometry approach to network visualization with ggplot2.
Multiple-geometries approach to plot network objects with ggplot2.
Grammar of graph graphics built in the spirit of ggplot2. See also:
tidygraph R package.
Layout algorithms based on the concept of stress majorization.
Estimate and simulate hierarchical exponential-family random graph models (HERGM) with local dependence.
Determine paths and states that social networks develop over time to form social hierarchies.
A collection of network analysis tools.
Compute various node centrality network measures by Burt, Borgatti and others.
Implements several network centrality measures.
Latent position and cluster models for network objects.
Linear programming model aimed at infering biological (signalling, gene) networks.
Tools to construct animated visualizations of dynamic network data in various formats.
Tools to analyze the network diffusion of innovations.
Up-to-date collection of network centrality indices, with lots of documentation.
Includes a review of relevant R packages.
Simulate and combine micro-models to research their impact on the macro-features of social networks.
Support for dynamic, (inter)temporal networks.
Tools to simulate bipartite networksgraphs with the degrees of the nodes fixed and specified.
Nonparametric estimation of preferential attachment and node fitness in temporal complex networks.
Implements Partial Correlation with Information Theory in order to identify meaningful correlations in weighted networks, such as gene co-expression networks.
Interface between R and recent versions of Cytoscape.
Tools to model and visualize psychometric networks; also aimed at weighted graphical models).
Tools to create sequence statistics from event lists to be used in
Estimate endogenous network effects in event sequences and fit relational event models (REM), which measure how networks form and evolve over time.