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@@ -135,13 +135,13 @@ The Science of a Connected Age</a></em>, by Duncan J. Watts (2003).</li>
</ul>
<h3 id="general-overviews">General Overviews</h3>
<ul>
<li><em><a
href="https://www.cambridge.org/us/academic/subjects/physics/statistical-physics/first-course-network-science">A
First Course in Network Science</a></em>, by Filippo Menczer, Santo
Fortunato, and Clayton A. Davis - Tutorials, datasets and other resouces
<a
href="https://github.com/CambridgeUniversityPress/FirstCourseNetworkScience">on
GitHub</a> (2020).</li>
<li><em><a href="https://hal.science/hal-04052709">L’analyse de réseau
en sciences sociales. Petit guide pratique</a></em>, by Laurent
Beauguitte, in French (2023). <a
href="https://beauguitte.github.io/analyse-de-reseau-en-shs/">Readable
online</a>.</li>
<li><em><a href="https://www.networkatlas.eu/">The Atlas for the
Aspiring Network Scientist</a></em>, by Michele Coscia (2021).</li>
<li><em><a
href="http://sk.sagepub.com/reference/socialnetworks">Encyclopedia of
Social Networks</a></em>, edited by George A. Barnett - Covers all sorts
@@ -151,11 +151,13 @@ network analysis (2011).</li>
href="https://www.springer.com/us/book/9781461461692">Encyclopedia of
Social Network Analysis and Mining</a></em>, edited by Reda Alhajj and
Jon Rokne (2014).</li>
<li><em><a href="https://hal.science/hal-04052709">L’analyse de réseau
en sciences sociales. Petit guide pratique</a></em>, by Laurent
Beauguitte, in French (2023). <a
href="https://beauguitte.github.io/analyse-de-reseau-en-shs/">Readable
online</a>.</li>
<li><em><a
href="https://www.cambridge.org/us/academic/subjects/physics/statistical-physics/first-course-network-science">A
First Course in Network Science</a></em>, by Filippo Menczer, Santo
Fortunato, and Clayton A. Davis - Tutorials, datasets and other resouces
<a
href="https://github.com/CambridgeUniversityPress/FirstCourseNetworkScience">on
GitHub</a> (2020).</li>
<li><em><a href="http://networksciencebook.com">Network
Science</a></em>, by Albert-László Barabási - Full book online
(2016).</li>
@@ -193,6 +195,9 @@ and Economic Networks</a></em>, by Matthew O. Jackson (2008).</li>
href="https://www.wiley.com/en-gb/Social+Network+Analysis+with+Applications-p-9781118169476">Social
Network Analysis with Applications</a></em>, by Ian McCulloh, Helen
Armstrong and Anthony Johnson (2013).</li>
<li><em><a href="https://olizardo.github.io/networks-textbook/">Social
Networks. An Introduction</a></em>, by Omar Lizardo and Isaac Jilbert -
free to read online (2023).</li>
<li><em><a
href="https://www.routledge.com/products/9780415458030">Social Networks:
An Introduction</a></em>, by Jeroen Bruggeman (<a
@@ -633,6 +638,9 @@ href="https://neo4j.het.io/browser/">Neo4j</a>.</li>
<li><a
href="https://CRAN.R-project.org/package=igraphdata">igraphdata</a> - R
data-centric package.</li>
<li><a
href="https://cran.r-project.org/package=igraphwalshdata">igraphwalshdata</a>
- Another R data-centric package.</li>
<li><a href="http://www.ecologia.ib.usp.br/iwdb/">Interaction Web
Database</a> - Ecological species interactions.</li>
<li><a
@@ -687,7 +695,7 @@ Datasets</a>.</li>
Datasets</a> - Network data obtained through the <a
href="http://www.sociopatterns.org/">SocioPatterns</a> sensing
platform.</li>
<li><a href="http://snap.stanford.edu/data/index.html">Stanford Large
<li><a href="https://snap.stanford.edu/data/index.html">Stanford Large
Network Dataset Collection</a>.</li>
<li><a href="https://ippsr.msu.edu/public-policy/state-networks">State
Networks</a> - US state-to-state relational variables, including
@@ -867,8 +875,9 @@ networks (“food webs”).</li>
<li><a href="http://mucha.web.unc.edu/networks/">Peter J. Mucha’s
Research Group at the University of North Carolina at Chapel
Hill</a>.</li>
<li><a href="http://sna.stanford.edu/">Social Network Analysis Group at
Stanford</a>.</li>
<li><a href="https://snap.stanford.edu/">Stanford Network Analysis
Project</a>, by <a href="https://cs.stanford.edu/~jure/">Jure
Leskovec</a>.</li>
<li><a href="http://warrencenter.upenn.edu/">Warren Center for Network
&amp; Data Sciences at the University of Pennsylvania</a>.</li>
<li><a href="http://yins.yale.edu/">Yale Institute for Network Science
@@ -952,6 +961,8 @@ Science Research Centre, Swansea University</a>.</li>
<li><a href="http://networkdynamics.org/">Network Dynamics</a> -
Research Lab at McGill University, led by <a
href="http://www.derekruths.com/">Derek Ruths</a></li>
<li><a href="https://nerds.itu.dk/">NEtwoRks, Data, and Society
(NERDS)</a> - Research group at IT University of Copenhagen.</li>
<li><a href="http://netzwerkerei.org/">Netzwerkerei</a> - Historical
research project on the connections between Jewish intellectuals.</li>
<li><a
@@ -1583,6 +1594,9 @@ of <a href="http://deim.urv.cat/~sergio.gomez/radalib.php">Radalib</a>,
a library written in Ada.</li>
<li><a href="https://ouestware.gitlab.io/retina">Retina</a> - Web
application to share GEXF and GraphML network visualizations.</li>
<li><a
href="https://github.com/sknetwork-team/scikit-network">Scikit-network</a>
- Open-source library for machine learning on graphs.</li>
<li><a href="https://www.sagemath.org/">SageMath</a> - Free open-source
mathematics software with extensive <a
href="http://doc.sagemath.org/html/en/reference/graphs/index.html">graph
@@ -1732,6 +1746,9 @@ Large-scale Graph Layout (formerly DrL)</a> - C++ algorithm, also
available as a <a
href="https://gephi.org/plugins/#/plugin/openord-layout">Gephi
plugin</a>.</li>
<li><a href="https://github.com/rapidsai/cugraph">RAPIDS cuGraph</a> -
Python packages and C/C++/CUDA libraries focused on GPU-accelerated
graph analytics.</li>
<li><a href="http://snap.stanford.edu/">Stanford Network Analysis
Project</a> - C++ general purpose network analysis and graph mining
library. Available as a Python library and in Microsoft Excel via
@@ -1941,6 +1958,9 @@ Cytoscape.js and Dash</li>
<li><a href="http://graph-tool.skewed.de/">graph-tool</a> - Python
module for network manipulation and analysis, written mostly in C++ for
speed.</li>
<li><a href="https://erivlis.github.io/graphinate/">Graphinate</a> -
Python package aimed at generating graphs from data sources, built on
top of <code>networkx</code>.</li>
<li><a href="https://pypi.python.org/pypi/graphviz">graphviz</a> -
Python renderer for the DOT graph drawing language.</li>
<li><a href="https://github.com/microsoft/graspologic">graspologic</a> -
@@ -1983,6 +2003,11 @@ graph measures, advanced visualizations, (geo)spatial tools, and
interfaces for neuroscience simulators.</li>
<li><a href="https://github.com/ike002jp/npartite">npartite</a> - Python
algorithms for community detection in n-partite networks.</li>
<li><a href="https://github.com/rraadd88/parag">parag</a> - Interactive
visualization of higher-order graphs in Python.</li>
<li><a href="https://www.pathpy.net/">pathpy</a> - Analysis of time
series data on networks using higher-order and multi-order graphical
models.</li>
<li><a
href="https://github.com/graphistry/pygraphistry">PyGraphistry</a> -
Python library to extract, transform, and visually explore big
@@ -1994,6 +2019,11 @@ href="https://perso.crans.org/aynaud/communities/">python-louvain</a> -
A solid implementation of Louvain community detection algorithm.</li>
<li><a href="https://www.raphtory.com/">Raphtory</a> - A platform for
building and analysing temporal networks.</li>
<li><a href="https://github.com/rapidsai/cugraph">RAPIDS cuGraph</a> -
Python packages and C/C++/CUDA libraries focused on GPU-accelerated
graph analytics.</li>
<li><a href="https://github.com/Qiskit/rustworkx">rustworkx</a> - A high
performance Python graph library implemented in Rust.</li>
<li><a
href="https://docs.scipy.org/doc/scipy/reference/sparse.csgraph.html#module-scipy.sparse.csgraph">scipy.sparse.csgraph</a>
- Fast graph algorithms based on sparse matrix representations.</li>
@@ -2146,6 +2176,11 @@ analysis tools.
Visualization with R and igraph</a> (2016).</li>
</ul></li>
<li><a
href="https://github.com/benyamindsmith/ig.degree.betweenness/">ig.degree.betweenness</a>
- an igraph implementation of the <a
href="https://arxiv.org/abs/2411.01394">Smith-Pittman</a> community
detection algorithm (2024).</li>
<li><a
href="https://CRAN.R-project.org/package=influenceR">influenceR</a> -
Compute various node centrality network measures by Burt, Borgatti and
others.</li>
@@ -2411,6 +2446,8 @@ Graph query language used by <a href="http://neo4j.com/">Neo4j</a>.</li>
or program.</p>
</blockquote>
<ul>
<li><a href="https://github.com/schochastics/centrality">A tutorial for
network centrality in R</a> (2023).</li>
<li><a href="http://kateto.net/sunbelt2016">Basic and Advanced Network
Visualization with Gephi and R</a> (2016).</li>
<li><a href="https://mr.schochastics.net/material/netAnaR/">Basic
@@ -2425,6 +2462,8 @@ and Palladio: Introductory Workshop</a> - Aimed at humanists
<li><a href="http://kateto.net/network-visualization">Static and Dynamic
Network Visualization with R</a> - Covers the igraph, network, ggraph,
network, networkD3, ndtv, threejs and visNetwork packages (2019).</li>
<li><a href="https://mr.schochastics.net/material/tidynetAnaR/">Tidy
Network Analysis in R using the tidygraph package</a> (2022).</li>
</ul>
<h2 id="varia">Varia</h2>
<blockquote>
@@ -2919,8 +2958,15 @@ href="https://github.com/m4rcs">Marc Schiller</a>, <a
href="https://tfardet.srht.site/">Tanguy Fardet</a>, <a
href="https://bernhardbieri.ch/">Bernhard Bieri</a>, <a
href="https://github.com/Yquetzal">Rémy Cazabet</a>, <a
href="https://github.com/JeremyGelb">Jeremy Gelb</a> and <a
href="https://github.com/mbastian">Mathieu Bastian</a> - have waived all
href="https://github.com/JeremyGelb">Jeremy Gelb</a>, <a
href="https://github.com/mbastian">Mathieu Bastian</a>, <a
href="https://github.com/mszell">Michael Szell</a>, <a
href="https://github.com/erivlis">Eran Rivlis</a>, <a
href="https://github.com/rraadd88">Rohan Dandage</a>, <a
href="https://github.com/benyamindsmith">Benjamin Smith</a>, <a
href="https://github.com/bduckles">Beth Duckles</a>, <a
href="https://github.com/cllei12">Lei Cao</a> and <a
href="https://www.simondelarue.com/">Simon Delarue</a> - have waived all
copyright and related or neighboring rights to this work.</p>
<p>Thanks to <a href="https://github.com/rjackland">Robert J.
Ackland</a>, <a href="https://cv.hal.science/laurent-beauguitte">Laurent
@@ -2941,3 +2987,6 @@ Snijders</a>, <a href="https://profiles.bu.edu/Christopher.Watson">Chris
Watson</a> and <a href="https://github.com/tawheeler">Tim A.
Wheeler</a>, who helped locating some of the awesome resources featured
in this list.</p>
<p><a
href="https://github.com/briatte/awesome-network-analysis">networkanalysis.md
Github</a></p>