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La "boîte à outils" du cartographe de l’information et des réseaux | #SNA #gephi #tools

La "boîte à outils" du cartographe de l’information et des réseaux | #SNA #gephi #tools | e-Xploration | Scoop.it
luiy's insight:

La "boîte à outils" du cartographe de l’information et des réseaux s’est sérieusement étoffée depuis quelques mois. De quoi équiper un peu plus encore une activité qui connaît quelques succès aujourd’hui, et dont on commence à comprendre le rôle essentiel pour les organisations et les territoires (en rappelant, comme à chaque fois, que le travail du cartographe d’informations commence là où finissent les données et finit là où commence l’interprétation des phénomènes). La nouveauté, cette fois-ci, est qu’il s’agit de deux "plateformes" en ligne et non plus seulement d’un plug-in ou d’une application isolée. Et, dans les deux cas, elles viennent enrichir les contextes d’utilisation de GEPHI (pour la 5e année en 2013 au Google Summer of Code, le fameux Gsoc). La preuve, si besoin était, que Gephi n’est pas une "application" mais un écosystème d’innovation permanente constituée d’une multitude d’acteurs.

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#Gephi plugin for depth-first searching for closed cycles on graphs | #SNA

#Gephi plugin for depth-first searching for closed cycles on graphs | #SNA | e-Xploration | Scoop.it
This free plugin for gephi traverses the active graph searching for closed walks, cycles and cliques. It can be used on both directed and undirected graphs.
luiy's insight:

This Gephi plugin traverses the active graph searching for closed walks, cycles and cliques. The search is made using the popular depth-first order search algorithm, using a standard single stack implementation made popular by Robert Sedgewick. Although this is very common in graph searching, there wasn’t a plugin for Gephi performing just this simple task and no more in a efficient way. Some features:

 

The plugin can be used on both directed and undirected graphs. In the first case, close walks (cycles) are hunted, while cliques in the latter; Reports include a distribution of the founded cycles by size; No use of external libraries: just 18k for the whole package; Asynchronous and interruptible task; Written in a pure OOP flavour, using Gephi APIs.
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#Pemex : Reforma Energética en México I #SNA #dataviz #sentiments

#Pemex : Reforma Energética en México I #SNA #dataviz #sentiments | e-Xploration | Scoop.it
Dataviz - Sentiments Analysis - Roles - Ego Network
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An Introduction to Mapping Company Networks Using #Gephi and OpenCorporates | #datajournalism

An Introduction to Mapping Company Networks Using #Gephi and OpenCorporates | #datajournalism | e-Xploration | Scoop.it
Evidence is Power
luiy's insight:

As more and more information about beneficial company ownership is made public under open license terms, we are likely to see an increase in the investigative use of this sort of data.

But how do we even start to work with such data? One way is to try to start making sense of it by visualising the networks that reveal themselves as we start to learn that company A has subsidiaries B and C, and major shareholdings in companies D, E and F, and that those companies in turn have ownership relationships with other companies or each other.

 

But how can we go about visualising such networks?!

This walkthrough shows one way, using company network data downloaded from OpenCorporates using OpenRefine, and then visualised using Gephi, a cross-platform desktop application for visualising large network data sets: Mapping Corporate Networks – Intro (slide deck version).

 

- See more at: http://schoolofdata.org/2013/11/15/an-introduction-to-mapping-company-networks-using-gephi-and-opencorporates-via-openrefine/#sthash.oX0ru7cD.dpuf

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Getting Historical Network Data into #Gephi --> #SNA #DH #dataviz #SNA_indatcom

Getting Historical Network Data into #Gephi --> #SNA #DH #dataviz #SNA_indatcom | e-Xploration | Scoop.it
I'm running a workshop next week on getting started with networks & gephi. Below, please find my first pass at a largely self-directed tutorial. This may eventually get incorporated into the Ma...
luiy's insight:

In the popup, under ‘available plugins’ look for ‘MultimodeNetworksTransformation’. Tick this box, then click on Install. Follow the instructions, ignore any warnings, click on ‘finish’. You may or may not need to restart Gephi to get the plugin running. If you suddenly see on the far right of ht Gephi window a new tab besid ‘statistics’, ‘filters’, called ‘Multimode Network’, then you’re ok.

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Graph Viz 101: Perceptual support of visualization - #dataviz #SNA #SNA_indatcom

Graph Viz 101: Perceptual support of visualization - #dataviz #SNA #SNA_indatcom | e-Xploration | Scoop.it
We are launching Graph Viz 101, a series of posts to teach the basics of graph visualization, written by Sébastien Heymann in collaboration with Bénédicte Le Grand of Université de Paris 1. This is our second post, please discuss it below!
luiy's insight:

Information visualization has been used to support social network analysis since the 1930s with the “sociogram” of J. Moreno (Moreno 1937), which is a graphic representation of social ties among a group of people. Despite the early beginning of network visuals, we had to wait until the 1990s and the democratization of computer graphics to see the development of interactive visualization software, which has made the interactive exploration of complex networks possible. Pajek (Batagelj 1998) is the most noticeable tool, as it provides both statistical algorithms and visual representations of social networks. Its methodological book entitled “Exploratory Social Network Analysis with Pajek” was published in 2005. The contribution of Information Visualization to science is stated in (Fekete 2008):

 

Information Visualization is meant at generating new insights and ideas that are the seeds of theories by using human perception as a very fast filter: if vision perceives some pattern, there might be a pattern in the data that reveals a structure. […] Therefore, it plays a special role in the sciences as an insight generating method.

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Investigación y desarrollo. Research and consulting. - Gephi Marketplace @luiy

Investigación y desarrollo. Research and consulting. - Gephi Marketplace @luiy | e-Xploration | Scoop.it
luiy's insight:

Gephi Marketplace @luiy


Design and development of services and products about knowledge analysis with Gephi.


- Collaboration analysis
- Organizations dynamics
- Learning analytics
- Knowledge management
- Social media analysis
- Roles and profiles
- Scientometrics
- Ethnographic models

 

Home page: http://viz.oycib.org/

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The Making of “History of #Rock in 100 Songs” | #dataviz #sna #gephi

The Making of “History of #Rock in 100 Songs” | #dataviz #sna #gephi | e-Xploration | Scoop.it
[This is a guest post by Susie Liu*, about the visualization project “History of Rock in 100 Songs”]
 
 
Figure 1. History of Rock in 100 Songs screenshot, live site here
 
The world of Rock ‘n’ Roll has always been very confusing to me.

Via ABoudières
luiy's insight:

When I found the Guardian’s list of 100 songs representative of rock music, I was inspired to use skills from my day job, creating data visualizations, to learn more about Rock ‘n’ Roll. With John as a domain expert to sanity check my work and a quick Google search of music APIs, we were ready to begin.

 

The original Guardian dataset only had the song title, artist, and release year of the song. I looked up more band information, such as its members and lifetime, using Last.fm and more song information, such as length and energy, using Echo Nest.

 

Exploring the data began with asking questions. I started simple. How do these songs appear over time? How do the timelines of the bands overlap with each other? I begin all of my visual brainstorming on paper like in Figure 2. It allows me to quickly see ideas. Plus, there is no hesitation to nix bad ideas because I’ve only invested a few minutes in the concept.

 

- See more at: http://visualoop.com/21745/the-making-of-history-of-rock-in-100-songs#sthash.9JUvGyoV.dpuf

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Visualising Related Entries in #Wikipedia Using #Gephi | #tutorial #SNA

Visualising Related Entries in #Wikipedia Using #Gephi | #tutorial #SNA | e-Xploration | Scoop.it
Sometime last week, @mediaczar tipped me off to a neat recipe on the wonderfully named Drunks&Lampposts blog, Graphing the history of philosophy, that uses Gephi to map an influence network in ...
luiy's insight:

To get DBpedia data into Gephi, we need to do three things:

 

- tell the importer where to find the data by giving it a URL (the “Driver” configuration setting);


- tell the importer what data we want to get back, by specifying what is essentially a database query (the “Request” configuration setting);


- tell Gephi how to create the network we want to visualise from the data returned from DBpedia (in the context of the “Request” configuration).

 

Fortunately, we don’t have to work out how to do this from scratch – from the Semantic Web ImportConfiguration panel, configure the importer by setting the configuration to DBPediaMovies.

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#MongoDB, #Neo4j and #Gephi project I #datascience

#MongoDB, #Neo4j and #Gephi project I #datascience | e-Xploration | Scoop.it
luiy's insight:

The first step in this process, presented by Showk, is importing the cables. Luckily, the WikiLeaks cables follow a simple structure that makes this relatively easy. Showk based his work on the cablegate Python code by Mark Matienzo that scrapes data from the cables in HTML form and converts this to Python objects. For the HTML scraping, the code is using Beautiful Soup, a well-known Python HTML/XML parser that automatically converts the web pages to Unicode and can cope with errors in the HTML tree. Moreover, with a SoupStrainer object, you can tell the Beautiful Soup parser to target a specific part of the document and forget about all the boilerplate parts such as the header, footer, sidebars, and supporting information.

 

After the parsing, The Python natural language toolkit NLTK is used on the text body to bring more structure to the word scramble with the goal of extracting some topics. The first step is tokenization: NLTK allows easily breaking up a text into sentences and each sentence into its separate words. Then for each word the stem is determined, which means that all words are grouped by their root. For example, to analyze the topics of the WikiLeaks cables, it doesn't matter if the word in a text is "language" or "languages", so they are both grouped by their root "languag". An SHA-256 hash value of each stem is then used as a database index.

 

MongoDB, a document-oriented database, is used as document storage for all this data. MongoDB allows transparently inserting and reading records as Python dictionaries, as well as automatic serializing and deserializing of the objects. Then Showk queried the MongoDB database to extract the heaviest occurrences and co-occurrences of words, and converted that to a graph using the Neo4j graph database.

 

For the final step, visualizing and analyzing the data, Bilcke used Gephi, an open source desktop application for the visualization of complex networks. Gephi, to which Bilcke is an active contributor, is a research-oriented graph visualization tool that has been used in the past to visualize some interesting graphs, like open source communities andsocial networks on LinkedIn. It's based on Java and OpenGL, but it also has a headless library, the Gephi Toolkit.

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#Gephi Plugin Developer Workshop | #SNA_Indatcom

Gephi Plugin Devleoper Workshop, October 6, 2011 in Mountain View, California. Presentation of Gephi's architecture and the different types of plugins that can
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Social Network Analysis & an Introduction to Tools | #dataviz #SNA_indatcom #SNA

This presentation covers the basics of network analysis and then goes into the different types of tool that support analyzing networks.

 
Via Stephen Dale, Kenneth Mikkelsen
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Stephen Dale's curator insight, July 21, 2013 7:41 AM

A great introduction to the power and benefits of SNA. Some useful pointers to SNA tools as well.

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Visualizando red FB con #Gephi | #sna_indatcom #dataviz

VISUALIZANDO NUESTRO FACEBOOK CON GEPHI Seminario de Integración y Producción – Digicom 2011
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