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README.md
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README.md
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### General Overviews
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- _[A First Course in Network Science](https://www.cambridge.org/us/academic/subjects/physics/statistical-physics/first-course-network-science)_, by Filippo Menczer, Santo Fortunato, and Clayton A. Davis - Tutorials, datasets and other resouces [on GitHub](https://github.com/CambridgeUniversityPress/FirstCourseNetworkScience) (2020).
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- _[Encyclopedia of Social Networks](http://sk.sagepub.com/reference/socialnetworks)_, edited by George A. Barnett - Covers all sorts of network-related themes (many of them not formal) as well as social network analysis (2011).
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- _[Encyclopedia of Social Network Analysis and Mining](https://www.springer.com/us/book/9781461461692)_, edited by Reda Alhajj and Jon Rokne (2014).
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- _[L'analyse de réseau en sciences sociales. Petit guide pratique](https://hal.science/hal-04052709)_, by Laurent Beauguitte, in French (2023).
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- _[Network Science](http://networksciencebook.com)_, by Albert-László Barabási - Full book online (2016).
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- _[Network Science](http://www.nap.edu/catalog/11516/network-science)_, by the U.S. National Research Council - Full book online (2005).
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- _[Network Science: Theory and Practice](http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1118211014.html)_, by Ted G. Lewis (2011).
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- _[Graph Theory](http://diestel-graph-theory.com/)_, by Reinhard Diestel - Full book online, also in Chinese and German (2016).
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- _[Graph Theory](http://www.dtic.mil/dtic/tr/fulltext/u2/705364.pdf)_, by Frank Harary - Full book online (1969).
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- _[Graphs & Digraphs](https://www.crcpress.com/Graphs--Digraphs-Sixth-Edition/Chartrand-Lesniak-Zhang/p/book/9781498735766)_, by Gary Chartrand, Linda Lesniak and Ping Zhang (2016).
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- _[Introduction to Combinatorics and Graph Theory](https://www.whitman.edu/mathematics/cgt_online/cgt.pdf)_, by Daniel Guichard - Full book online (2016).
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- _[Introduction to Combinatorics and Graph Theory](https://www.whitman.edu/mathematics/cgt_online/cgt.pdf)_, by David Guichard - Full book online (2016).
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- _[Modern Graph Theory](https://www.springer.com/us/book/9780387984889)_, by Belá Bollobás (1998).
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### Method-specific
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- [Polinode](https://www.polinode.com/) - Web-based platform to both analyze network data as well as collect network data via relationship-based surveys.
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- [PUCK - Program for the Use and Computation of Kinship data](http://www.kintip.net/) - Cross-platform Java program for genealogical network analysis.
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- [Radatools](http://deim.urv.cat/~sergio.gomez/radatools.php) - Set of tools intended for the analysis of complex networks, built on top of [Radalib](http://deim.urv.cat/~sergio.gomez/radalib.php), a library written in Ada.
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- [Retina](https://ouestware.gitlab.io/retina) - Web application to share GEXF and GraphML network visualizations.
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- [SageMath](http://www.sagemath.org/) - Free open-source mathematics software with extensive [graph capabilities](http://doc.sagemath.org/html/en/reference/graphs/index.html).
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- [Segrada](http://segrada.org/) - Cross-platform tool to build and visualize semantic graph databases.
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- [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.
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> See also [Social Network Analysis with Python](https://www.youtube.com/watch?v=qgGqaBAEy3Q), a 3-hour tutorial by Maksim Tsvetovat and Alex Kouznetsov given at PyCon US 2012 ([code](https://github.com/maksim2042/PyCon2012)).
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> For more awesome Python packages, see the [Awesome Python](https://github.com/vinta/awesome-python) and [Awesome Python Books](https://github.com/Junnplus/awesome-python-books) lists.
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- [bokeh](https://bokeh.org/) - Python library for interactive data visualization in the browser, with support for networks.
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- [dash-cytoscape](https://github.com/plotly/dash-cytoscape) - Interactive network visualization library in Python, powered by Cytoscape.js and Dash
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- [graph-tool](http://graph-tool.skewed.de/) - Python module for network manipulation and analysis, written mostly in C++ for speed.
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- [graphviz](https://pypi.python.org/pypi/graphviz) - Python renderer for the DOT graph drawing language.
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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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- [Implementing an ERGM from Scratch in Python](https://gist.github.com/dmasad/8509304), using networkx and numpy (2014).
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- [nxviz](https://github.com/ericmjl/nxviz/) - Visualization package for NetworkX.
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- [nngt](https://nngt.readthedocs.io) - Library-agnostic graph generation and analysis that wraps around `networkx`, `igraph` and `graph-tool`). Includes normalized graph measures, advanced visualizations, (geo)spatial tools, and interfaces for neuroscience simulators.
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- [npartite](https://github.com/ike002jp/npartite) - Python algorithms for community detection in n-partite networks.
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- [PyGraphistry](https://github.com/graphistry/pygraphistry) - Python library to extract, transform, and visually explore big graphs.
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- [python-igraph](http://igraph.org/python/) - Python version of the igraph network analysis package.
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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 – by chronological order: [François Briatte](http://f.briatte.org/),
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To the extent possible under law, the authors of this list – by chronological order: [François Briatte](https://f.briatte.org/),
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[Ian McCulloh](https://www.linkedin.com/in/mcculloh),
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[Aditya Khanna](http://home.uchicago.edu/~khanna7),
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[Manlio De Domenico](https://comunelab.fbk.eu/manlio/),
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@ -965,9 +970,13 @@ Alden S. Klovdahl,
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[David Schoch](http://mr.schochastics.net/),
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[Jaewon Chung](https://github.com/j1c),
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[Benedek Rozemberczki](https://github.com/benedekrozemberczki),
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[Alex Loftus](https://github.com/loftusa) and
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[Arun](https://github.com/arunppsg),
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[Bernhard Bieri](https://bernhardbieri.ch/) – have waived all copyright and related or neighboring rights to this work.
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[Alex Loftus](https://github.com/loftusa),
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[Arun](https://github.com/arunppsg),
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[Filippo Menczer](https://cnets.indiana.edu/fil/),
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[Marc Schiller](https://github.com/m4rcs),
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[Tanguy Fardet](https://tfardet.srht.site/) and
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[Bernhard Bieri](https://bernhardbieri.ch/) -
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have waived all copyright and related or neighboring rights to this work.
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Thanks to [Robert J. Ackland](https://github.com/rjackland),
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[Laurent Beauguitte](https://cv.archives-ouvertes.fr/laurent-beauguitte),
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