> Inspired by [Awesome Deep Learning](https://github.com/ChristosChristofidis/awesome-deep-learning) and [Awesome Math](https://github.com/rossant/awesome-math).
-_[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 (2010).
- _[Réseaux sociaux et structures relationnelles](https://www.puf.com/content/R%C3%A9seaux_sociaux_et_structures_relationnelles)_, by Emmanuel Lazega, in French (2014).
-_[Social Network Analysis. Methods and Applications](http://www.cambridge.org/ar/academic/subjects/sociology/sociology-general-interest/social-network-analysis-methods-and-applications)_, by Stanley Wasserman and Katherine Faust (1994).
-_[Studying Social Networks. A Guide to Empirical Research](http://press.uchicago.edu/ucp/books/book/distributed/S/bo15475096.html)_, by Marina Hennig _et al._ (2013).
1._[Graph Theory](http://www.cs.unibo.it/babaoglu/courses/cas00-01/tutorials/GraphTheory.pdf)_, by Reinhard Diestel - Full electronic version online (2000).
1._[Exponential Random Graph Models for Social Networks](http://www.cambridge.org/9780521193566)_, edited by Dean Lusher, Johan Koskinen and Garry Robins (2013).
-_[Multilevel Network Analysis for the Social Sciences](https://www.springer.com/fr/book/9783319245188)_, edited by Emmanuel Lazega and Tom A.B. Snijders (2016).
-_[Network Analysis: Methodological Foundations](https://www.springer.com/fr/book/9783540249795)_, edited by Ulrik Brandes and Thomas Erlebach - Covers network centrality, clustering, blockmodels, spatial networks and more (2005).
-_[Political Networks. The Structural Perspective](http://www.cambridge.org/ar/academic/subjects/sociology/political-sociology/political-networks-structural-perspective)_, by David Knoke (1994).
1._[Analyzing Social Networks](https://sites.google.com/site/analyzingsocialnetworks/)_ (using UCINET), by Stephen P. Borgatti, Martin G. Everett and Jeffrey C. Johnson (2013).
1._[Neighbor Networks. Competitive Advantage Local and Personal](https://global.oup.com/academic/product/neighbor-networks-9780199570690)_, by Ronald S. Burt (2010).
-_[Comparing Policy Networks. Labor Politics in the U.S., Germany, and Japan](http://www.cambridge.org/ar/academic/subjects/politics-international-relations/comparative-politics/comparing-policy-networks-labor-politics-us-germany-and-japan)_, by David Knoke _et al._ (1996).
- [Graph Theory and Applications](http://www.hamilton.ie/ollie/Downloads/Graph.pdf), by Paul Van Dooren - Full lecture slides (Hamilton Institute, Dublin, 2009).
- [Graph Theory: Penn State Math 485 Lecture Notes](http://www.personal.psu.edu/cxg286/Math485.pdf), by Christopher Griffin - Full lecture notes (Penn State University, 2012).
- [Networks, Complexity and Its Applications](http://ocw.mit.edu/courses/media-arts-and-sciences/mas-961-networks-complexity-and-its-applications-spring-2011/), by Cesar Hidalgo (MIT, 2011).
- [Political Networks: Methods and Applications](http://vanity.dss.ucdavis.edu/~maoz/networks/Spring%202011/pol279-11.htm), by Zeev Maoz (University of California in Davis, 2012).
- [Social and Economic Networks: Models and Analysis](https://www.coursera.org/course/networksonline), by Matthew O. Jackson (Stanford University via Coursera, 2015).
> See also [Mangal](http://mangal.io/), an online platform and collection of tools to analyze, archive and share ecological network data ([preprint](http://biorxiv.org/content/early/2015/02/24/002634), [Python package](https://github.com/mangal-wg/pymangal), [R package](https://github.com/mangal-wg/rmangal)).
1. [AFS RT 26 “Réseaux sociaux”](http://www.cmh.pro.ens.fr/reseaux-sociaux/) - Thematic Network of the French Sociological Association, in French.
- [ECPR Political Networks SG](https://politicalnetsecpr.wordpress.com/) - Standing Group of the European Consortium for Political Research ([Twitter account](https://twitter.com/politicalnets)).
- [GDR Analyse de réseaux en sciences humaines et sociales](http://arshs.hypotheses.org/), in French.
- [Groupe FMR - Flux, Matrices, Réseaux](http://groupefmr.hypotheses.org/), in French.
1. "[Graph Theory and Networks in Biology](http://dx.doi.org/10.1049/iet-syb:20060038)" ([preprint](http://arxiv.org/abs/q-bio/0604006); _IET Systems Biology_, 2007).
- "[Network Analysis and Political Science](http://www.annualreviews.org/doi/abs/10.1146/annurev.polisci.12.040907.115949)" (_Annual Review of Political Science_, 2011).
- "[Statistical Models for Social Networks](http://www.annualreviews.org/doi/abs/10.1146/annurev.soc.012809.102709)" (_Annual Review of Sociology_, 2011).
> See also the [Social Network Analysis Project Survey](https://docs.google.com/spreadsheets/d/1Xo-ehJatzmxMek6gPG0h-d7yRSuiO6_flViTQNMAku0/edit#gid=0) ([blog post](http://pudo.org/blog/2013/12/21/sna-survey.html)), an earlier attempt to chart social network analysis tools, which links to many commercial platforms not included in this list, such as [Detective.io](http://www.detective.io/).
- [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.
- [Pajek](http://vlado.fmf.uni-lj.si/pub/networks/pajek/) - Windows program for large network analysis, free for noncommercial use.
- [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.
- [Siena](http://www.stats.ox.ac.uk/~snijders/siena/) - Simulation Investigation for Empirical Network Analysis. Formerly a Windows program, now developed as the RSiena R package.
- [SoNIA](http://web.stanford.edu/group/sonia/) (Social Network Image Animator) - Tool to visualize dynamic or longitudinal network data. Formerly a [Java program](https://sourceforge.net/projects/sonia/), now developed as the ndtv R package.
- [vbmod: Variational Bayesian Inference for Network Modularity](http://vbmod.sourceforge.net/) - MATLAB and Python implementations of the [Bayesian community detection algorithm](http://arxiv.org/abs/0709.3512).
- [weighted-modularity-LPAwbPLUS](https://github.com/sjbeckett/weighted-modularity-LPAwbPLUS) - Julia, MATLAB and R implementations of two algorithms to find weighted modularity in bipartite networks.
### C / C++
1. [Boost Graph Library (BGL)](http://www.boost.org/doc/libs/1_60_0/libs/graph/doc/) - C++ library that provides a generic interface to access graph structures.
- [igraph](http://igraph.org/) - C library of network analysis tools; also exists as packages for Python and R.
- [Louvain Method](https://sites.google.com/site/findcommunities/) - C++ code for the [Louvain multi-level community detection algorithm](http://arxiv.org/abs/0803.0476).
- [networks.tb](http://networks-tb.sourceforge.net/) - C program designed for analyzing socio-semantic networks. Runs on Linux and Mac OSX.
- [Stanford Network Analysis Project](http://snap.stanford.edu/) - C++ general purpose network analysis and graph mining library. Available as a Python library and in Microsoft Excel via NodeXL.
- [Walktrap](https://www-complexnetworks.lip6.fr/~latapy/PP/walktrap.html) - C++ program that implements the [WalkTrap community detection algorithm](http://arxiv.org/abs/physics/0512106).
- [jLouvain](https://github.com/upphiminn/jLouvain) - Louvain community detection for Javascript ([example](http://bl.ocks.org/emeeks/125db75c9b55ddcbdeb5)).
- [Sigma](http://sigmajs.org/) - JavaScript library dedicated to graph drawing.
> Most items below are from [a Google spreadsheet](https://docs.google.com/spreadsheets/d/1vJILk2EW1JnR3YAwTSSqAV5mPkeXaezy45wOoafBpfU/edit#gid=0) by Michał Bojanowski and others.
> For more awesome Python packages, see the [Awesome Python](https://github.com/vinta/awesome-python) list.
- [networkx](http://networkx.github.io/) - Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
> See also [this Google spreadsheet](https://docs.google.com/spreadsheets/d/1CoFGtrW85D9FsVcAE5-bcXVl6QOTncwXjFBYp4u2WgE/edit?usp=sharing) by Ian McCulloh and others.
> For more awesome R resources, see the [Awesome R](https://github.com/qinwf/awesome-R) and [Awesome R Books](https://github.com/RomanTsegelskyi/rbooks) lists.
- [concoR](https://github.com/aslez/concoR) - A translation of the CONCOR network blockmodeling algorithm ([blog post](http://badhessian.org/2015/05/concor-in-r/)).
- [ContentStructure](https://github.com/matthewjdenny/ContentStructure) - implements an extension to the [Topic-Partitioned Multinetwork Embeddings (TPME) model](http://dirichlet.net/pdf/krafft12topic-partitioned.pdf).
- [GERGM](https://cran.r-project.org/web/packages/GERGM/) - Estimation and diagnosis of the convergence of Generalized Exponential Random Graph Models (GERGM).
- [hergm](https://cran.r-project.org/web/packages/hergm/) - Estimate and simulate hierarchical exponential-family random graph models (HERGM) with local dependence.
- [latentnet](https://cran.r-project.org/web/packages/latentnet/) - Latent position and cluster models for network objects.
- [networkD3](http://christophergandrud.github.io/networkD3/) - D3 JavaScript network graphs from R.
- [ndtv](https://cran.r-project.org/web/packages/ndtv/) - Tools to construct animated visualizations of dynamic network data in various formats.
- [network](https://cran.r-project.org/web/packages/network/) - Basic tools to manipulate relational data in R.
- [networkDynamic](https://cran.r-project.org/web/packages/networkDynamic/) - Support for dynamic, (inter)temporal networks.
- [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.
- [Rgraphviz](https://bioconductor.org/packages/release/bioc/html/Rgraphviz.html) - Support for using the Graphviz library and its [DOT](http://www.graphviz.org/doc/info/lang.html) language from within R.
- [spectralGOF](http://people.bu.edu/jccs/spectralGOF.html) - Compute the "spectral goodness of fit" (SGOF), a measure of how well a network model explains the structure of an observed network.
- [statnet](http://statnet.org/) - The project behind many R network analysis packages ([mailing-list](https://mailman.u.washington.edu/mailman/listinfo/statnet_help)).
- [tergm](https://cran.r-project.org/web/packages/tergm/) - Fit, simulate and diagnose models for temporal exponential-family random graph models (TERGM).
- [Lessons on Exponential Random Graph Modeling from _Grey’s Anatomy_ hook-ups](http://badhessian.org/2012/09/lessons-on-exponential-random-graph-modeling-from-greys-anatomy-hook-ups/) (2012).
- [Working with Bipartite/Affiliation Network Data in R](https://solomonmessing.wordpress.com/2012/09/30/working-with-bipartiteaffiliation-network-data-in-r/) (2012).
- [Basic Notions for the Analysis of Large Two-mode Networks](https://www-complexnetworks.lip6.fr/~latapy/Publis/socnet07.pdf) - Introduction to bipartite network analysis ([related code](https://www-complexnetworks.lip6.fr/~latapy/Bip/)).
- [Blog Posts About Networks by Pierre Mercklé](http://pierremerckle.fr/category/reseaux/), in French.
- [Center for Network Science](http://cns.ceu.edu/) - A research center with a PhD in Network Science program at the Central European University in Budapest.
- [David Knoke on Network Analysis](https://thesocietypages.org/methods/2015/01/30/david-knoke-on-network-analysis/) - A 20-minute interview that discusses the uses and benefits of network analysis, drawing upon Knoke's research on terrorist networks.
- [How Small is the World, Really?](https://medium.com/@duncanjwatts/how-small-is-the-world-really-736fa21808ba#.kyr90lhyo) - A discussion of "x degrees of separation" small-world experiments.
- [How to Draw Graphs in LaTeX?](https://tex.stackexchange.com/questions/57152/how-to-draw-graphs-in-latex) - An illustration of how to use [PGF/TikZ](https://en.wikipedia.org/wiki/PGF/TikZ) to draw graphs in the [LaTeX](https://latex-project.org/) typesetting environment.
- [Interdependence in Governance and Policy](https://sites.psu.edu/desmaraisgroup/) - Network-oriented research group led by Bruce A. Desmarais at Penn State University.
- [Patterns in the Ivy: The Small World of Metal](http://badhessian.org/2013/09/patterns-in-the-ivy-the-small-world-of-metal/) - An example of a two-mode network analysis based on metal artists and bands.
- [The Performativity of Networks](http://kieranhealy.org/files/papers/performativity.pdf) - A paper that connects network theory to the sociology of science.
- [Peter J. Mucha's Research Group at the University of North Carolina at Chapel Hill](http://mucha.web.unc.edu/networks/) - As it says on the box.
- [Social Network Analysis Group @ Stanford](http://sna.stanford.edu/) - As it says on the box.
- [Social Network Analysis Software](https://en.wikipedia.org/wiki/Social_network_analysis_software) - Wikipedia English entry with links to many commercial and often outdated software.
- [Star Wars Social Networks: The Force Awakens](http://evelinag.com/blog/2016/01-25-social-network-force-awakens/index.html) - An example of a social network analysis written in F#.
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.
Remember that an awesome list has to be, well, awesome. The "[Awesome Manifesto](https://github.com/sindresorhus/awesome/blob/master/awesome.md)" states:
> __Only awesome is awesome__
>
> 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.
>
> ...
>
> __Comment on why something is awesome__
>
> 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.
To the extent possible under law, the authors of this list – by chronological order: [François Briatte](http://f.briatte.org/), [Ian McCulloh](https://www.linkedin.com/in/mcculloh), [Aditya Khanna](http://home.uchicago.edu/~khanna7), [Manlio De Domenico](http://deim.urv.cat/~manlio.dedomenico/index.php), Patrick Kaminski, [Ericka Menchen-Trevino](http://www.ericka.cc/) – have waived all copyright and related or neighboring rights to this work.
