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Related:  Network ScienceOutils d'analyse du corpus

Data Visualization Software | Tulip Quelques outils pour visualiser les réseaux sociaux L’analyse des réseaux sociaux permet de mieux comprendre le comportement des acteurs et des communautés : quelle est la place de l’acteur au sein de l’ensemble ? Est-il central ? périphérique ? Fait-il le lien entre différentes communautés ? Comment est organisée la communauté ? Cette analyse permet de comprendre en profondeur le fonctionnement des communautés en ligne. L’analyse des réseaux sociaux se fait en trois temps distincts : la récupération des données, leur analyse et leur visualisation. Sur de petits graphes, il est possible de faire la récupération des données a la main. Les données qui sont récupérées concernent le lien : qui est lié à qui ou à quoi, mais on pourra également s’intéresser au volume d’information produits, à sa fréquence et faire quelques corrélations. Navicrawler est une extension Firefox qui explore le contenu et la structure des pages web. Guess est surtout un outil de rendu, mais il permet également de faire quelques calcul. Le tutorial de Guess

The DIMES project | Join the journey to map the Internet, download the DIMES agent today Navicrawler | WebAtlas UPDATE: There now a portable version of Firefox with Navicrawler included: More information on these: These folders are zipped. Unzip and run “Firefox Portable”. Regular versions: You can download the Navicrawler 1.7 or the Navicrawler 1.8b (now hosted directly on The Navicrawler is no longer supported. In this “next generation Navicrawler” you will be able to dynamically change the boundaries of every website, to have graphs with pages and websites at the same time, and to declare aliases (the same website with different domain names). Until then, the most reliable way to use the Navicrawler is probably to install Firefox 3.6 and the Navicrawler 1.7 (you might be able to install both versions of Firefox, the old one for the Navicrawler and the last one for you). Documentation (in French): The version 1.8 (and above) use a toolbar button to launch the sidebar.

1+1=1 : la formule des réseaux On parle de réseau lorsque des éléments interagissent entre eux au sein d’un groupe. Ils sont étudiés aussi bien par les sciences humaines et sociales, les sciences du vivant et de la terre, que les sciences et techniques de l'information et de la communication. De façon étonnante, tous ces réseaux apparemment distincts ont certains points communs. Ce texte cherche à proposer une synthèse accessible à des non-spécialistes de ce qui est commun (mais aussi différent) dans les différents types de réseaux. La triade « constituants, règles, réseau » Souvent nous tentons d’aborder un réseau social, technique ou autre par le réductionnisme : en étudiant le comportement de ses constituants. Deux hommes veulent se confronter au tir à la corde. Les constituants plus les règles donnent le réseau Le réseau peut être déterminé par ses constituants et ses règles. En fait il faut considérer les trois aspects avec deux d’entre eux déterminant le troisième. La perte (partielle) de notre capacité à prévoir

GUESS: The Graph Exploration System Math algorithm tracks crime, rumours, epidemics to source ( -- A team of EPFL scientists has developed an algorithm that can identify the source of an epidemic or information circulating within a network, a method that could also be used to help with criminal investigations. Investigators are well aware of how difficult it is to trace an unlawful act to its source. The job was arguably easier with old, Mafia-style criminal organizations, as their hierarchical structures more or less resembled predictable family trees. In the Internet age, however, the networks used by organized criminals have changed. Innumerable nodes and connections escalate the complexity of these networks, making it ever more difficult to root out the guilty party. EPFL researcher Pedro Pinto of the Audiovisual Communications Laboratory and his colleagues have developed an algorithm that could become a valuable ally for investigators, criminal or otherwise, as long as a network is involved. The validity of this method thus has been proven a posteriori.

Social network analysis software Social network analysis software (SNA software) is software which facilitates quantitative or qualitative analysis of social networks, by describing features of a network either through numerical or visual representation. Overview[edit] Some SNA software can perform predictive analysis.[5] This includes using network phenomena such as a tie to predict individual level outcomes (often called peer influence or contagion modeling), using individual-level phenomena to predict network outcomes such as the formation of a tie/edge (often called homophily models[6]) or particular type of triad, or using network phenomena to predict other network phenomena, such as using a triad formation at time 0 to predict tie formation at time 1. Network analysis software generally consists of either packages based on graphical user interfaces (GUIs), or packages built for scripting/programming languages. Interactive Data Visualization technology often includes social network analysis capabilities. Notes

New research to uncover nuances of networks Feb. 20, 2013 9:01 a.m. When a species disappears from a region, the rest of the ecosystem may flourish or collapse, depending on the role that species played. When a storm rolls across the coast, the power grid might reconfigure itself quickly or leave cities dark for days. A snowstorm might mean business as usual in a hardy city and a severe food shortage in another, depending on the distribution strategies of residents. Each of these systems is a kind of network, with thousands of members and relationships linking them. With current network theory, scientists can predict a few simple trends, such as which web pages are likely to get more hits over time. A new four-year, $2.9 million grant from the Defense Advanced Research Projects Agency is supporting SFI research that will, the researchers hope, propel their understanding of networks to the next level. Nodes and links in real networks are cloaked in details, he says. They have already made progress.

NodeXL: Network Overview, Discovery and Exploration for Excel - Home US Military Scientists Solve the Fundamental Problem of Viral Marketing Viral messages begin life by infecting a few individuals and then start to spread across a network. The most infectious end up contaminating more or less everybody. Just how and why this happens is the subject of much study and debate. Network scientists know that key factors are the rate at which people become infected, the “connectedness” of the network and how the seed group of individuals, who first become infected, are linked to the rest. It is this seed group that fascinates everybody from marketers wanting to sell Viagra to epidemiologists wanting to study the spread of HIV. So a way of finding seed groups in a given social network would surely be a useful trick, not to mention a valuable one. These guys have found a way to identify a seed group that, when infected, can spread a message across an entire network. Their method is relatively straightforward. This process finishes when there is nobody left in the network who has more friends than the threshold. Expect to hear more!

Gephi, an open source graph visualization and manipulation software