Commit History · panisson/pygephi_graphstreaming
Un graphe dynamique et interactif avec d3.js Billet publié le 03/11/2012 R est un logiciel formidable. Mais d’autres outils sont plus adaptés pour une présentation sur internet.
This post lays out some of the importance of interactivity for network diagrams and we think is well worth a read (or at least a skim!); however, if you wish to skip to the demos, these are linked at the end of the post. Visualizing network data is a prime example of a research activity where both desktop tools and online libraries exist, but are not well connected with one another. Desktop software like NodeXL and Gephi provide the ability to collect and visualize network data (users on Twitter, videos on YouTube, etc.). These applications, however, provide limited facilities for hosting, sharing, and optimizing visualizations for the web. Interactive Visualizations | For teaching, research, and dissemination
Visualising Advocacy | Drawing by Numbers
Social network analysis often amounts to calculating the statistics on a graph like this: the number of edges (friends) connected to a particular node (person), and the distribution of the number of edges connected to nodes across the entire graph. When the graph consists of up to 10 billion elements (nodes and edges), such computations can be done on a single server with dedicated graph software like Neo4j. But bigger networks — like Facebook's social network, which is a graph with more than 60 billion elements — require a distributed solution. Marko A. Rodriguez, a graph consultant with Aurelius, shows in a blog post how to use R and Hadoop (integrated with Revolution Analytics' RHadoop packages) to analyze Facebook-scale social networks. He first simulates a social network (shown at the top of this post) using R's igraph package, and then distributed the network in the Hadoop cluster with to.dfs function (from the rhdfs package). Facebook-class social network analysis with R and Hadoop
Google Fusion Tables (ci-dessus, une carte des Etats-Unis montrant le pourcentage de foyers ayant un accès Internet en 2007, par états, d'après le bureau américain du recensement) Vous avez des données à explorer ? Voici quelques outils qui pourront vous être utiles pour les transformer en informations et en graphiques attrayants.
clustering - How to do community detection in a weighted social network/graph? - Statistical Analysis - Stack Exchange
After learning the basics of R, I decided to learn something harder last week. I picked Social Network Analysis (SNA) to learn the concepts of SNA and R. My primary interest in SNA is visual exploration of networks, so I needed to find a tool first. Enterprise Software Doesn't Have to Suck: Social Network Analysis using R and Gephis
SocialAction is a social network analysis tool that integrates visualization and statistics to improve the analytical process. A journal article about SocialAction was recently published in IEEE Computer Graphics and Applications. See the full details in the papers below. SocialAction won a VAST Mini-Challenge award for uncovering hidden structure in social networks over time. There are also two recent conference publications about SocialAction! SocialAction
software for social network analysis Huisman, Mark and van Duijn, Marijtje A.J. (2011). A reader's guide to SNA software. In J. Scott and P.J. Carrington (Eds.) The SAGE Handbook of Social Network Analysis (pp. 578-600).
A comparative study of social network analysis tools
The Music Technology Playground from Last.fm
Find Your Influencers : KXEN Find Your Influencers It’s no assumption that people socialize into groups. By using business data, we can learn about the links between our customers and just as importantly, which customers have a strong social influence. We can use this insight to create a competitive advantage.
Social Network Analysis for telecoms & gaming. Reduce Churn & Improve Marketing Front
The purpose of the DyNet project is to develop the equivalent of a flight simulator for reasoning about dynamic networked organizations. Through a unique blending of computer science, social networks and organization theory we are creating a new class of tools for managing organizational dynamics. The core tool is DyNet - a reasoning support tool for reasoning under varying levels of uncertainty about dynamic networked and cellular organizations, their vulnerabilities, and their ability to reconstitute themselves. Using DyNet the analyst would be able to see how the networked organization was likely to evolve if left alone, how its performance could be affected by various information warfare and isolation strategies, and how robust those strategies were in the face of varying levels of information assurance. DyNet Software | CASOS
[CFinder] Clusters and Communities: Overlapping dense groups in networks
Commetrix - Dynamic Network Visualization Software - Dynamic Visualization of Networks - Dynamic Social Network Analysis Software Visualization - Dynamic Network Analysis - Virtual Communities
yEd is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams. Create diagrams manually, or import your external data for analysis. Our automatic layout algorithms arrange even large data sets with just the press of a button.
Home Welcome to the UCINET website UCINET is a social network analysis program developed by Steve Borgatti, Martin Everett and Lin Freeman. The program is distributed by Analytic Technologies.
In January 2008 this page was replaced by Pajek Wiki. Pajek runs on Windows and is free for noncommercial use. DOWNLOAD Pajek Data: test networks, GPHs, GEDs, PDB files. Screenshots; History; Manual (pdf); Papers/presentations; Applications; in News; Examples: SVG, PDF.