Outils d'analyse

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Un graphe dynamique et interactif avec d3.js 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.
D3.js - Data-Driven Documents D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG and CSS. D3’s emphasis on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data-driven approach to DOM manipulation. Download the latest version here: d3.v3.zip Or, to link directly to the latest release, copy this snippet:

D3.js - Data-Driven Documents

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 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 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.

22 outils gratuits pour visualiser et analyser les données (1ère partie)

22 outils gratuits pour visualiser et analyser les données (1ère partie)
Python Data Analysis Library — pandas: Python Data Analysis Library pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. 0.13.0 released (January 15, 2014) The new major 0.13 release is out.

Python Data Analysis Library — pandas: Python Data Analysis Library

current community your communities Sign up or log in to customize your list. clustering - How to do community detection in a weighted social network/graph? - Statistical Analysis - Stack Exchange 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

Enterprise Software Doesn't Have to Suck: Social Network Analysis using R and Gephis

SocialAction 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 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
NETDRAW

22 outils gratuits pour visualiser et analyser les données (2ème partie)

La bibliothèque JavaScript InfoVis Toolkit propose des graphiques très peaufinés Vous avez des données à explorer ? Voici quelques outils qui pourront vous être utiles pour les transformer en informations et en graphiques attrayants. Pour faire parler des données, rien ne vaut une panoplie d'outils de visualisation graphique.
NodeXL is a free, open-source template for Microsoft® Excel® 2007, 2010 and (possibly) 2013 that makes it easy to explore network graphs. With NodeXL, you can enter a network edge list in a worksheet, click a button and see your graph, all in the familiar environment of the Excel window. Visit the NodeXL Graph Gallery to see the wide variety of graphs that have been created by the NodeXL community. What's New The latest release enhances NodeXL's Twitter Search Network feature by expanding the network to include all people who were replied to or mentioned by the people who tweeted the search term, but who didn't tweet the search term themselves.

NodeXL: Network Overview, Discovery and Exploration for Excel

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
DyNet Software | CASOS
[CFinder] Clusters and Communities: Overlapping dense groups in networks
AnTools

Gephi

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