GraphStream is a graph handling Java library that focuses on the dynamics aspects of graphs. Its main focus is on the modeling of dynamic interaction networks of various sizes. In addition, GraphStream provides a way to handle the graph evolution in time. This means handling the way nodes and edges are added and removed, and the way data attributes may appear, disappear and evolve. In order to handle dynamic graphs, the library defines in addition to graph structures the notion of “stream of graph events”.


GraphStream will be presented by one of its leading developers, Yoann Pigne. Yoann is an assistant professor at the University of Le Havre France. His work focuses on the modeling and simulation of interaction networks in various fields such transportation systems or mobile ad hoc networks.



graph-tool is a module for very fast manipulation and statistical analysis of networks in Python. The core of the library is written in C++, with many algorithms supporting parallel processing on multi-core architectures. The library allows for rich annotated graph data structures, many standard graph algorithms, as well as inference of generative network models. In addition, graph-tool allows for effective interactive visualizations of networks.

tiago.peixotograph-tool will be persented by its creator, Tiago P. Peixoto. Tiago is currently a post-doc at the University of Bremen. His research interests include complex networks and statistical mechanics.



igraph is one of the most popular libraries for graph analysis and manipulation. Written in C/C++ and available also for Python and R, the library is very popular amongs academics because it greatly speeds up experiments, exploratory analysis of networks, and helps visualizing networks efficiently. Key features of igraph include generators for a wide variety of network models, algorithms for computing centrality measures, ease of integration with high-level programming languages, and portability. Of course, igraph is a free software as well.

katherine.ognyanovaR/igraph will be presented by Katherine Ognyanova. Katya is an Assistant Professor at the School of Communication and Information, Rutgers University. She does work in the areas of computational social science and network analysis. Prior to her appointment at Rutgers, Katya was a postdoctoral researcher at the Lazer Lab, Northeastern University and a fellow at the Institute for Quantitative Social Science, Harvard University.



Unfortunately, due to a scheduling conflict, prof. Brandes will not be able to deliver the workshop on Sunday. However, if you are interested in learning more about visone, please come to the second session of the School of Code on Monday, 1:20pm – 2:40pm, in Conference Room “B”. Ulrik Brandes will give a 40 minute presentation of the tool and will discuss its research potential.

Visone is a free tool for network visualization and analysis. Its primary focus is on research and teaching of network analysis. It offers novel visualization layouts for large networks, provides means of analyzing unconfirmed relations, and supports complex analysis of event networks.

ulrik.brandesVisone will be presented by its creator, prof. Ulrik Brandes. Professor Brandes needs no introduction in the SNA community. He is the author of countless papers on graph visualization and graph algorithms, his work has been published in top scientific journals and conferences. His contribution to the field includes the most popular algorithm for betweenness computation, the idea of social clocks, and numerous advances in graph visualization techniques.



NetworkX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. It offers many different algorithms for graph manipulation, analysis, and visualization. Multiple generators for classic networks, random graphs or social networks make working with the package easy and fun. NetworkX is free, fully documented, with many tutorials and examples, distributed on the BSD Licence.

ben.edwardsThe tutorial on NetworkX will be given by Ben Edwards. Ben is currently a doctoral student at the University of New Mexico and one of the most active developers of NetworkX. His dissertation is focused on building abstract and data driven models which analyze cyber interventions in cybersecurity.