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193 lines
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Markdown
193 lines
14 KiB
Markdown
# Awesome Network Analysis [](https://github.com/sindresorhus/awesome)
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An [awesome list](https://github.com/sindresorhus/awesome) of resources to construct, analyze and visualize network data.
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## Table of Contents
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- __[Books](#books)__
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- __[Overviews](#overviews)__
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- __[Language-specific](#language-specific)__
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- __[Method-specific](#method-specific)__
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- __[Topic-specific](#topic-specific)__
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- __[Courses](#courses)__
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- __[Datasets](#datasets)__
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- __[Journals](#journals)__
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- __[Professional groups](#professional-groups)__
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- __[Review Articles](#review-articles)__
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- __[Software](#software)__
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- __[JavaScript](#javascript)__
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- __[Python](#python)__
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- __[R](#r)__
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- __[Tutorials](#tutorials)__
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- __[Varia](#varia)__
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- __[Contribution Guidelines](#contribution-guidelines)__
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## Books
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### Overviews
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1. _[Networks. An Introduction](http://www-personal.umich.edu/~mejn/networks-an-introduction/)_, by Mark E.J. Newman (2010).
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- _[Networks, Crowds, and Markets: Reasoning About a Highly Connected World](http://www.cs.cornell.edu/home/kleinber/networks-book/)_, by David Easley and Jon Kleinberg; complete pre-publication draft online (2010).
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- _[Réseaux sociaux et structures relationnelles](https://www.puf.com/content/R%C3%A9seaux_sociaux_et_structures_relationnelles)_, by Emmanuel Lazega, in French (2014).
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- _[Sociologie des réseaux sociaux](http://pierremerckle.fr/2011/02/sociologie-des-reseaux-sociaux/)_, by Pierre Mercklé, in French (2011).
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### Method-specific
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1. _[Multilevel Network Analysis for the Social Sciences](https://www.springer.com/fr/book/9783319245188)_, by Emmanuel Lazega and Tom A.B. Snijders (2016).
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### Software-specific
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1. _[Analyzing Social Networks](https://sites.google.com/site/analyzingsocialnetworks/)_ (using UCINET), by Stephen P. Borgatti, Martin G. Everett and Jeffrey C. Johnson (2013).
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2. _[Statistical Analysis of Network Data with R](http://www.springer.com/us/book/9781493909827)_, by Eric D. Kolaczyk and Gabor Csárdi (2014).
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### Topic-specific
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1. _[Neighbor Networks. Competitive Advantage Local and Personal](https://global.oup.com/academic/product/neighbor-networks-9780199570690)_, by Ronald S. Burt (2010).
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## Courses
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1. [Complex Networks](https://www.uvm.edu/~pdodds/teaching/courses/2016-01UVM-303/), by Peter Sheridan Dodds (2016).
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## Datasets
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1. [KONECT - The Koblenz Network Collection](http://konect.uni-koblenz.de/).
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- [Stanford Large Network Dataset Collection](http://snap.stanford.edu/data/index.html).
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- [tnet Datasets](https://toreopsahl.com/datasets/).
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- [UCI Network Data Repository](http://networkdata.ics.uci.edu/).
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## Journals
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1. _[Applied Network Science](http://appliednetsci.springeropen.com/)_ (Springer Open).
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- _[Computational Social Networks](http://computationalsocialnetworks.springeropen.com/)_ (Springer Open).
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- _[Connections](http://www.insna.org/connections.html)_ (INSNA).
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- _[Journal of Complex Networks](http://comnet.oxfordjournals.org/)_ (Oxford).
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- _[Journal of Social Structure](http://www.cmu.edu/joss)_ (INSNA).
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- _[Network Science](http://journals.cambridge.org/action/displayJournal?jid=nws)_ (Cambridge).
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- _[REDES](http://revista-redes.rediris.es/)_, in Spanish (INSNA).
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- _[Social Network Analysis and Mining](http://link.springer.com/journal/13278)_ (Springer).
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- _[Social Networks](http://ees.elsevier.com/son/default.asp)_ (Elsevier).
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## Professional groups
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1. [AFS RT 26 “Réseaux sociaux”](http://www.cmh.pro.ens.fr/reseaux-sociaux/) - Thematic Network of the French Sociological Association, in French.
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- [ECPR Political Networks SG](https://politicalnetsecpr.wordpress.com/) - Standing Group of the European Consortium for Political Research ([Twitter account](https://twitter.com/politicalnets)).
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- [GDR Analyse de réseaux en sciences humaines et sociales](http://arshs.hypotheses.org/), in French.
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- [Groupe FMR - Flux, Matrices, Réseaux](http://groupefmr.hypotheses.org/), in French.
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- [INSNA: International Network for Social Network Analysis](http://www.insna.org/) ([mailing-list](http://www.insna.org/pubs/socnet.html)).
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- [NetSci: Network Science Society](http://www.netscisociety.net/).
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- [APSA Political Networks](http://www.polinetworks.org/) - Organized Section of the American Political Science Association.
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## Review Articles
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1. "[Network Analysis and Political Science](http://www.annualreviews.org/doi/abs/10.1146/annurev.polisci.12.040907.115949)" (_Annual Review of Political Science_, 2011).
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- "[Statistical Models for Social Networks](http://www.annualreviews.org/doi/abs/10.1146/annurev.soc.012809.102709)" (_Annual Review of Sociology_, 2011).
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## Software
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1. [Cytoscape](http://www.cytoscape.org/) - Cross-platform Java program to build, analyze and visualize networks.
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- [Discourse Network Analyzer (DNA)](http://www.philipleifeld.com/discourse-network-analyzer/discourse-network-analyzer-dna.html) - Qualitative content analysis tool with network export facilities, written in Java with R integration.
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- [Gephi](https://gephi.github.io/) - Cross-platform, free and open source tool for network visualization.
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- [GraphViz](http://www.graphviz.org/) - Software to draw graphs in the [DOT](http://www.graphviz.org/doc/info/lang.html) language.
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- [networks.tb](http://networks-tb.sourceforge.net/) - A suite designed for analyzing socio-semantic networks, written in C.
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- [NodeXL](http://nodexl.codeplex.com/) - Free, open-source template for Microsoft Excel to explore network graphs.
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- [Pajek](http://vlado.fmf.uni-lj.si/pub/networks/pajek/) - Windows program for large network analysis, free for noncommercial use.
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- [PNet](http://www.swinburne.edu.au/fbl/research/transformative-innovation/our-research/MelNet-social-network-group/PNet-software/index.html) - Simulation and estimation of exponential random graph models (ERGMs), written in Java for Windows.
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- [Siena](http://www.stats.ox.ac.uk/~snijders/siena/) - Simulation Investigation for Empirical Network Analysis, formerly a Windows program, now an R package.
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- [Stanford Network Analysis Project](http://snap.stanford.edu/) - C++ general purpose network analysis and graph mining library; available as a Python library and through NodeXL.
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- [UCINET](https://sites.google.com/site/ucinetsoftware/) - Windows commercial software package for the analysis of social network data.
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- [VOSviewer](http://www.vosviewer.com/) - Cross-platform software tool for constructing and visualizing bibliometric networks, written in Java.
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### JavaScript
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> For more awesome Python packages, see the [Awesome JavaScript](https://github.com/sorrycc/awesome-javascript) list.
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- [d3.js](https://d3js.org/) - JavaScript visualization library that can plot [force-directed graphs](http://bl.ocks.org/mbostock/4062045).
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- [jLouvain](https://github.com/upphiminn/jLouvain) - Louvain community detection for Javascript ([example](http://bl.ocks.org/emeeks/125db75c9b55ddcbdeb5)).
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- [Sigma](http://sigmajs.org/) - JavaScript library dedicated to graph drawing.
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- [vis.js](http://visjs.org/) - JavaScript library with network visualization capabilities.
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### Python
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> Most items below are from [a Google spreadsheet](https://docs.google.com/spreadsheets/d/1vJILk2EW1JnR3YAwTSSqAV5mPkeXaezy45wOoafBpfU/edit#gid=0) by Michał Bojanowski and others.
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> For more awesome Python packages, see the [Awesome Python](https://github.com/vinta/awesome-python) list.
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1. [graphviz](https://pypi.python.org/pypi/graphviz) - Python renderer for the DOT graph drawing language.
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- [linkpred](https://github.com/rafguns/linkpred) - Assess the likelihood of potential links in a future snapshot of a network.
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- [networkx](http://networkx.github.io/) - Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
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- [python-igraph](http://igraph.org/python/) - Python version of the igraph network analysis package.
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### R
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> See also [this Google spreadsheet](https://docs.google.com/spreadsheets/d/1CoFGtrW85D9FsVcAE5-bcXVl6QOTncwXjFBYp4u2WgE/edit?usp=sharing) by Ian McCulloh and others.
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> For more awesome R packages, see the [Awesome R](https://github.com/qinwf/awesome-R) list.
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- [Bergm](https://cran.r-project.org/web/packages/Bergm/) - Tools to analyse Bayesian exponential random graph models.
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- [ergm](https://cran.r-project.org/web/packages/ergm/) - Estimation of Exponential Random Graph Models.
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- [GERGM](https://cran.r-project.org/web/packages/GERGM/) - Estimation and diagnosis of the convergence of Generalized Exponential Random Graph Models (GERGM).
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- [hergm](https://cran.r-project.org/web/packages/hergm/) - Estimate and simulate hierarchical exponential-family random graph models with local dependence.
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- [igraph](http://igraph.org/r/) - A collection of network analysis tools.
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- [latentnet](https://cran.r-project.org/web/packages/latentnet/) - Latent position and cluster models for network objects.
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- [networkD3](http://christophergandrud.github.io/networkD3/) - D3 JavaScript network graphs from R.
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- [ndtv](https://cran.r-project.org/web/packages/ndtv/) - Tools to construct animated visualizations of dynamic network data in various formats.
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- [network](https://cran.r-project.org/web/packages/network/) - Basic tools to manipulate relational data in R.
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- [networkDynamic](https://cran.r-project.org/web/packages/networkDynamic/) - Support for dynamic, (inter)temporal networks.
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- [rgexf](https://bitbucket.org/gvegayon/rgexf/wiki/Home) - Export network objects from R to [GEXF](http://gexf.net/format/), for manipulation with network software like Gephi or Sigma.
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- [RSiena](https://cran.r-project.org/web/packages/RSiena/) - Simulation Investigation for Empirical Network Analysis; fits models to longitudinal network data.
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- [sna](https://cran.r-project.org/web/packages/sna/) - Basic network measures and visualization tools.
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- [spnet](http://cran.r-project.org/web/packages/spnet/) - Methods for dealing with spatial social networks.
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- [statnet](http://statnet.org/) - The project behind many R network analysis packages.
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- [tnet](https://cran.r-project.org/web/packages/tnet/) - Network measures for weighted, two-mode and longitudinal networks.
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- [tsna](https://cran.r-project.org/web/packages/tsna/) - Tools for temporal social network analysis.
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- [visNetwork](https://github.com/DataKnowledge/visNetwork) - Using vis.js library for network visualization.
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- [xergm](https://cran.r-project.org/web/packages/xergm/) - Extensions of Exponential Random Graph Models.
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## Tutorials
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1. [Analyse des réseaux : une introduction à Pajek](http://quanti.hypotheses.org/512/), in French (2011).
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- [Basic and Advanced Network Visualization with Gephi and R](http://kateto.net/sunbelt2016) (Sunbelt 2016).
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- [Exponential Random Graph Models (ERGMs) Using statnet](https://statnet.org/trac/raw-attachment/wiki/Sunbelt2015/ergm_tutorial.html) (Sunbelt 2015).
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- [Guides for Using the statnet Package](http://www.melissaclarkson.com/resources/R_guides/) (2010).
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- [Implementing an ERGM From Scratch in Python](http://davidmasad.com/blog/ergms-from-scratch/) (2014).
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- [L'analyse des graphes bipartis](https://halshs.archives-ouvertes.fr/FMR/halshs-00794976), in French (2013).
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- [La détection de communautés avec Pajek 3.6](http://groupefmr.hypotheses.org/544), in French (2012).
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- [Modeling Valued Networks with statnet](https://statnet.org/trac/raw-attachment/wiki/Sunbelt2013/Valued.pdf) (Sunbelt 2013).
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- [Network Analysis and Visualization with R and igraph](http://kateto.net/networks-r-igraph) (NetSciX 2016).
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- [Practical Social Network Analysis With Gephi](http://derekgreene.com/gephitutorial/) (2014).
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- [Static and Dynamic Network Visualization with R](http://kateto.net/network-visualization) (PolNet 2015).
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- [Working with Bipartite/Affiliation Network Data in R](https://solomonmessing.wordpress.com/2012/09/30/working-with-bipartiteaffiliation-network-data-in-r/) (2012).
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## Varia
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- [Blog posts about networks](http://pierremerckle.fr/category/reseaux/) by Pierre Mercklé, in French.
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- [Network Fact](https://twitter.com/networkfact) - A Twitter account about networks, graph theory, and related topics.
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- [Videos from the Political Networks 2009 conference](https://vimeo.com/user2690333).
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## Contribution Guidelines
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Please contribute to this list by sending a [pull request](https://github.com/briatte/awesome-network-analysis/pulls) after reading the [Contribution Guidelines](https://github.com/sindresorhus/awesome/blob/master/contributing.md) for stylistic indications.
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- __All sources are organized alphabetically__ with date and language mentions when relevant.
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- __Authors__ are mentioned for books and courses only.
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- __To cite R packages__, please cite the stable CRAN version when it exists.
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- __To cite Python packages__, please cite the PyPi version when it exists.
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Remember that an awesome list has to be, well, awesome. The "[Awesome Manifesto](https://github.com/sindresorhus/awesome/blob/master/awesome.md)" states:
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> __Only awesome is awesome__
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>
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> Research if the stuff you're including is actually awesome. Put only stuff on the list you or another contributor can personally recommend and rather leave stuff out than include too much.
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>
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> ...
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>
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> __Comment on why something is awesome__
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>
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> Apart from suggesting a particular item on your list, you should also inform your readers why it's on the list and how they will benefit from it.
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Please also add your name to the copyright waiver below.
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## License
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[](http://creativecommons.org/publicdomain/zero/1.0/)
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To the extent possible under law, the authors of this list ([François Briatte](http://f.briatte.org/)) have waived all copyright and related or neighboring rights to this work.
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