NodeXL The simplest, easiest way to get insights into networks, try the free and open NodeXL! Network Overview Discovery and Exploration for Excel 2007/2010/2013 NodeXL provides support for social network analysis in the context of a spreadsheet. See: NodeXL is a project from the Social Media Research Foundation and is a collaboration among: NodeXL is the free and open add-in for Excel that supports network overview, discovery and exploration. NodeXL requires Office 2007, 2010 or 2013. A video tutorial for NodeXL can be found at: A book Analyzing Social Media Networks with NodeXL: Insights from a connected world is available from Morgan-Kaufmann: Analyzing Social Media Networks with NodeXL: Insights from a Connected World Supporting documentation can be found at Data sets and other teaching materials are available at Social Media Research Related Publications
Interactive Dynamics for Visual Analysis Graphics Jeffrey Heer, Stanford University Ben Shneiderman, University of Maryland, College Park The increasing scale and availability of digital data provides an extraordinary resource for informing public policy, scientific discovery, business strategy, and even our personal lives. To get the most out of such data, however, users must be able to make sense of it: to pursue questions, uncover patterns of interest, and identify (and potentially correct) errors. In concert with data-management systems and statistical algorithms, analysis requires contextualized human judgments regarding the domain-specific significance of the clusters, trends, and outliers discovered in data. Visualization provides a powerful means of making sense of data. The goal of this article is to assist designers, researchers, professional analysts, procurement officers, educators, and students in evaluating and creating visual analysis tools. Some visualization system designers have explored alternative approaches.
GUESS: The Graph Exploration System Small-world network Small-world network exampleHubs are bigger than other nodes Average vertex degree = 1,917 Average shortest path length = 1.803. Clusterization coefficient = 0.522 Random graph Average vertex degree = 1,417 Average shortest path length = 2.109. Clusterization coefficient = 0.167 In the context of a social network, this results in the small world phenomenon of strangers being linked by a mutual acquaintance. Properties of small-world networks[edit] This property is often analyzed by considering the fraction of nodes in the network that have a particular number of connections going into them (the degree distribution of the network). ) is defined as R. Examples of small-world networks[edit] Small-world properties are found in many real-world phenomena, including road maps, food chains, electric power grids, metabolite processing networks, networks of brain neurons, voter networks, telephone call graphs, and social influence networks. Examples of non-small-world networks[edit] See also[edit]
Data Visualization Software | Tulip Cytoscape: An Open Source Platform for Complex Network Analysis and Visualization NodeXL: Network Overview, Discovery and Exploration for Excel - Home Connected: The Power of Six Degrees A very rich documentary about the new science of network. It is built around reproducing the “Six degrees of separation” experience. The main concepts are well explained and the history of discoveries is emphasized with many examples and interviews of the researchers. The first part is about small worlds model and explaining why six degrees works. Warning: the video is no longer available, due to right owner’s decision to remove it from vimeo. EDIT: Video available here To go further : Found here. Related Posts: No related posts. Networks ~ how kevin bacon cured cancer Networks six degrees Trackback
Gephi, an open source graph visualization and manipulation software Fast Thinking and Slow Thinking Visualisation Last week I attended the Association of American Geographers Annual Conference and heard a talk by Robert Groves, Director of the US Census Bureau. Aside the impressiveness of the bureau’s work I was struck by how Groves conceived of visualisations as requiring either fast thinking or slow thinking. Fast thinking data visualisations offer a clear message without the need for the viewer to spend more than a few seconds exploring them. These tend to be much simpler in appearance, such as my map of the distance that London Underground trains travel during rush hour. The explicit message of this map is that surprisingly large distances are covered across the network and that the Central Line rolling stock travels furthest. It is up to the reader to work out why this may be the case. or the seemingly impenetrable (from a distance at least), but wonderfully intricate hand drawn work of Steven Walter (click image for interactive version).
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 ? 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. Navicrawler n’assurant que la récolte des données, leur traitement doit se faire avec un autre programme : Pajek, Guess, Network Workbench Tool, ou NodeXL. Le tutorial de Guess WordPress: J'aime chargement…
Network Science Course - 2011 1/10 Introduction to Network Science We are surrounded by systems that are hopelessly complex, from the society, a collection of seven billion individuals, to communications systems, integrating billions of devices, from computers to cell phones. Our very existence is rooted in the ability of thousands of genes to work together in a seamless fashion; our thoughts, reasoning, and our ability to comprehend the world surrounding us is hidden in the coherent activity of billions of neurons in our brain. 1/19 Bio – Networks Internet Biological networks are an essence of life. 1/24 Random Graph Theory Networks and graphs: In its simplest form, a network is a set of nodes connected by links. 1/26 Movie Night View The documentary trailer... 1/31 Random Networks (Project discussion) The first basic question we need to answer is the following: if you are given a network, how do you think of it? 2/2 The Small World Its a small world after all. 2/7 Scale Free Networks 2/9 Generating Functions 2/14 Prof.