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antropologiaNet, dataviz, collective intelligence, algorithms, social learning, social change, digital humanities
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Un chercheur révèle l'ampleur du conspirationnisme sur YouTube | #SNA #DDJ #algorithmes

Un chercheur révèle l'ampleur du conspirationnisme sur YouTube | #SNA #DDJ #algorithmes | e-Xploration | Scoop.it

Jonathan Albright, directeur de recherche au Tow Center for Digital Journalism, et data journaliste, a plongé dans les entrailles de YouTube pour mener l'enquête. En partant du mot-clé « crisis actor », en référence à la théorie du complot née après la tuerie de Parkland, il a abouti, via l’outil de recommandation de YouTube, à un réseau de 8 842 vidéos dont la majorité recèlent une théorie conspirationniste, et qui cumulent au total 4 milliards de vues. Sa conclusion ? Une profonde inquiétude, alors que plusieurs chercheurs ont déjà mis en évidence les effets pervers des algorithmes de recommandation de la plateforme, qui augmentent l'exposition de l’internaute à des contenus de plus en plus radicaux.

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Cartographie 2017. Les Acteurs du Patrimoine Culturel Immatériel | #PCI #dataviz

Cartographie 2017. Les Acteurs du Patrimoine Culturel Immatériel | #PCI #dataviz | e-Xploration | Scoop.it
The protection of the Intangible Cultural Heritage of UNESCO is ensured by a complex network of actors: institutions, associations, groups and individuals. The goal of this project is to understand which are the main actors in France and monitor over time the interactions between them. Web mapping has been identified as the most suitable methodology for this analysis. This method relies on the underlying idea that hyperlinks between web sites can be used as representations of social connections.
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Facebook data collection and photo network visualization with Gephi and R | #SNA #dataviz #Gephi

Facebook data collection and photo network visualization with Gephi and R | #SNA #dataviz #Gephi | e-Xploration | Scoop.it
Collecting and visualizing Facebook networks using people's profile photos as node images (three ways: with Gephi, igraph, or qgraph). Includes the steps to generate the visualization along with an R script.
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Barabási Albert-László - Books

Barabási Albert-László - Books | e-Xploration | Scoop.it

Network Science


ALBERT-LÁSZLÓ BARABÁSI


Networks are everywhere, from the Internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and the social sciences, introduces network science to an interdisciplinary audience. From the origins of the six degrees of separation to explaining why networks are robust to random failures, the author explores how viruses like Ebola and H1N1 spread, and why it is that our friends have more friends than we do. Using numerous real-world examples, this innovatively designed text includes clear delineation between undergraduate and graduate level material. The mathematical formulas and derivations are included within Advanced Topics sections, enabling use at a range of levels. Extensive online resources, including films and software for network analysis, make this a multifaceted companion for anyone with an interest in network science.

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Interactive flow visualization in R

Interactive flow visualization in R | e-Xploration | Scoop.it
Exploring flows between origins and destinations visually is a common task, but can be difficult to get right. In R, there are many tutorials on the web that show how to produce static flow maps (see here, here, here, and here, among others).

Over the past couple years, R developers have created an infrastructure to bridge R with JavaScript using the htmlwidgets package, allowing for the generation of interactive web visualizations straight from R. I’d like to demonstrate here a few examples for exploratory interactive flow graphics that use this infrastructure.
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Graph Commons – Map networks together

Graph Commons – Map networks together | e-Xploration | Scoop.it
Graph Commons is a collaborative platform for making, analyzing and publishing network maps.
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Tommaso Venturini / we love #networks, mais pourquoi ? I #SNA

SÉMINAIRE 2012 DE L’ERG : ENTRETIEN INFINI - ART ET SCIENCES (QUELS DIALOGUES ?) les 5, 6 et 7 mars 2012 / de 10h à 23h Halles de Schaerbeek,…
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Connecting the Dots Behind the 2016 Candidates | #ddj #politics

Connecting the Dots Behind the 2016 Candidates | #ddj #politics | e-Xploration | Scoop.it
How the teams behind some likely and announced 2016 candidates are connected to previous campaigns, administrations and organizations.

Via Dominique Cardon
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Abridged List of #MachineLearning Topics. #Resources #tools #datascience

Abridged List of #MachineLearning Topics. #Resources #tools #datascience | e-Xploration | Scoop.it
luiy's insight:

- Deep learning is a set of algorithms in machine learning that attempt to model high-level abstractions in data by using model architectures composed of multiple non-linear transformations.

 

- Online machine learning is a model of induction that learns one instance at a time thus reducing the amount of memory required.

 

- Natural Language Toolkit (NLTK) - a leading tool for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning.

 

-Computer Vision. OpenCV – popular computer vision library designed to by computational efficiency with a strong focus on real-time applications.

 

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Davos on Twitter: who do the attendees follow? | #dataviz #SNA

Davos on Twitter: who do the attendees follow? | #dataviz #SNA | e-Xploration | Scoop.it

Via ukituki
luiy's insight:

Every year, the World Economic Forum brings together the most recognisable figures of business and politics. With all eyes on Davos, we decided to turn the optics upside down and see who the twitterati gathered in Switzerland follow on social media.


The inner ring of circles represent the 20 most-followed accounts by Davos attendees, while the outer circles are individual attendees.

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ukituki's curator insight, January 22, 2015 10:39 AM

Network Visualization by Finanacial Times

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Linkedin inMaps discontinued : how to visualize your professional network now? | #SNA via @Linkurious

Linkedin inMaps discontinued : how to visualize your professional network now? | #SNA via @Linkurious | e-Xploration | Scoop.it
How to replace Linkedin inMaps and visualize your professional network with Gephi.
luiy's insight:

One of the cool not-so-known feature of Linkedin was the ability to visualize your professional network. This was provided via inMaps and allowed everyone to get a feel of the communities and influencers in his own network. On August 31 this service will be discontinued but you can still visualize your Linkedin network.

 

 

Collect your data

 

First step first. We need to collect the information about our connections and their relationships. The good news is that Linkedin has a nice API anyone can use. The bad news is that this API only allows us to see our connections and the connections between them. Just like with inMaps, we will not be able to see the individuals we are not connected to.

 

We are going to need to register a new application with Linkedin to be able to use its API. Simply go here and sign in with your account (you do have an account, right?).

 

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Text Visualization Browser | #dataviz #sna #datascience

Text Visualization Browser | #dataviz #sna #datascience | e-Xploration | Scoop.it
Text Visualization Browser
luiy's insight:
Text Visualization BrowserDeveloped by Kostiantyn Kucher and Andreas KerrenISOVIS group, Linnaeus University, Växjö, SwedenCheck out our IEEE VIS 2014 poster abstract
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DareDo's curator insight, October 30, 2014 6:07 AM

De multiples manières de visualiser des textes...

Sans doute devrions-nous réfléchir à des manières simples d'organiser nos propres textes et nos ressources.

A creuser certainement...

Stephen Dale's curator insight, November 7, 2014 11:23 AM

A Visual Survey of Text Visualization Techniques. Excellent resource.

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#Complexity in Social Networks | #algorithms #SNA

#Complexity in Social Networks | #algorithms #SNA | e-Xploration | Scoop.it
How network structure impacts consumer experience.
luiy's insight:

In the same way software has “eaten” many industries and continues to devour more, the structure of complex systems is relevant in an increasing number of subjects, from neurobiology to industrial engineering. In the consumer internet, many of the most interesting technology platforms are, at their core, networks. As with most complex systems, small changes can have large consequences, and the structure of a network can materially impact consumer experience, many times changing the core way that people interact with the service.

 

One way to think about these technology platforms is to think of any complex network as having four fundamental components:

 

- Nodes (the objects in the graph, e.g., people, things)

 

- Data/content (the thing being shared between the nodes, e.g., tweet

 

- Edges with rules (e.g., bidirectional “friend”, single-directional “follow”)

 

- Jumping functions, specifically ways to transmit the data/content from one subgroup of people to another on the same platform, usually based on rules surrounding how the edges are structured (e.g., retweeting / liking / favoriting).

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From the assembly line to your home: 17 years of robots | by @Quid | #Robotics #SNA #Networks

From the assembly line to your home: 17 years of robots | by @Quid | #Robotics #SNA #Networks | e-Xploration | Scoop.it

This is a network map of over 2700 robotics companies founded since 2000. 


This post is based on a talk Will Weisman, Executive Director of Summits at Singularity University, gave at the SU Global Summit where he used Quid to visualize the evolution of the robotics startup landscape during his introduction to exponential technologies.

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The ICIJ Releases Neo4j Desktop Download of Paradise Papers

The ICIJ Releases Neo4j Desktop Download of Paradise Papers | e-Xploration | Scoop.it
Explore the entire Paradise Papers dataset for yourself as a Neo4j Desktop package, now available for download from the Pulitzer Prize-winning ICIJ.
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Connected: The Power of Six Degrees - YouTube I #networks #SNA

CONNECTED: THE POWER OF SIX DEGREES (alternate title: How Kevin Bacon Cured Cancer) is a 2008 documentary film by Annamaria Talas. It was first aired in 2009 on the Science Channel. The documentary introduces the audience to the main ideas of network science through the exploration of the concept of six degrees of separation. Stars: Nyaloka Auma, Kevin Bacon, Albert-László Barabás
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- Topogram - Visualize how networks change over time and space

- Topogram - Visualize how networks change over time and space | e-Xploration | Scoop.it

"Topogram"

Topogram is a web-based app to visualize the evolution of networks over time and space.



Try it online at app.topogram.io or install your own.

Features
Time-based navigation in graph
Network layouts + geographic data
Online/real-time data update via API

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Interactive timeline of the PRISM scandal - Virostatiq

Interactive timeline of the PRISM scandal - Virostatiq | e-Xploration | Scoop.it

Constructing the visualization.


The visualization was constructed entirely in HTML5 and JavaScript. Four major libraries were used: 


-  Sigma.js for displaying the networks. The latest version does not contain some key functionality for dynamically and additively loading and unloading of subgraphs into the main graph, so the source code was updated with required methods. Separate article on that topic is upcoming. 


- Three.js for rotating Earth and all geographically-related work. Simile Timeline for the timeline.


- Flot for the bar graph.

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56Kast #94 – Archiver les réactions numériques aux attentats

► Abonnez-vous : http://bit.ly/abo56kast La chercheuse Valérie Schafer coordonne le projet Asap, qui veut analyser les réactions des internautes au
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#Visualizing the network of Donald #Trump - @Linkurious - Understand the connections in your data I #publicpolicy #SNA

#Visualizing the network of Donald #Trump - @Linkurious - Understand the connections in your data I #publicpolicy #SNA | e-Xploration | Scoop.it

On January 15, BuzzFeed released a large dataset of Donald Trump’s connections, including people, organizations and the nature of their relationships.

In their article “Help Us Map TrumpWorld”, the four authors of the investigation, John Templon, Anthony Cormier, Alex Campbell and Jeremy Singer-Vine, asked the public to help them understand and analyse the data.

Now we are asking the public to use our data to find connections we may have missed, and to give us context we don’t currently understand. We hope you will help us — and the public — learn more about TrumpWorld and how this unprecedented array of businesses might affect public policy.”


So we decided to see what it would looks like in Linkurious, our graph analysis and visualization tool.

The dataset is publicly available in a Google spreadsheet. We imported it in a Neo4j graph database using the following script inspired by Michael Hunger’s work:

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How MIT Visualizes Supply Chain Risk | #SNA #predictive

How MIT Visualizes Supply Chain Risk | #SNA #predictive | e-Xploration | Scoop.it
MIT Supply Chain Management Director Bruce Arntzen discusses risk visualization and Sourcemap [Video]

 

How does a company keep tabs on thousands of suppliers? That’s the question Bruce Arntzen tried to answer when he started the Hi-Viz Research Project. As Executive Director of MIT’s Supply Chain Management Program, Arntzen works with corporations to find innovative solutions to supply chain problems. The idea for the Hi-Viz project came during a 2011 meeting of the Supply Chain Risk Leadership Council. A survey of attendees listed Supply Chain Visibility as the top concern. Why? With thousands of suppliers and sub-suppliers, it can be very time-consuming to find the weakest link in a supply chain. Arntzen’s solution: an automatic visualization of the end-to-end supply chain where the weakest links could be seen in real time. Watch his interview to learn how MIT and Sourcemap developed the first automated risk visualization [more details below the fold].

 

In 2015, the Hi-Viz project is partnering with actuarial data providers to provide predictive risk analytics. Sourcemap is making available inventory risk mapping as part of its enterprise software-as-a-service. Want to get involved? Learn more about the Hi-Viz project, or contact Sourcemap for a demo.

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TULIP : Data Visualization Software | #SNA #dataviz

TULIP : Data Visualization Software | #SNA #dataviz | e-Xploration | Scoop.it
Tulip is a software system dedicated to the visualization of huge graphs. It enables, 3D visualizations, 3D modifications, plugin support, support for clusters and navigation, and automatic graph drawing.
luiy's insight:

Tulip is an information visualization framework dedicated to the analysis and visualization of relational data. Tulip aims to provide the developer with a complete library, supporting the design of interactive information visualization applications for relational data that can be tailored to the problems he or she is addressing. 

 

Written in C++ the framework enables the development of algorithms, visual encodings, interaction techniques, data models, and domain-specific visualizations. One of the goal of Tulip is to facilitates the reuse of components and allows the developers to focus on programming their application. This development pipeline makes the framework efficient for research prototyping as well as the development of end-user applications.

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OpenGraphiti : Data Visualization Framework | #SNA #open #dataviz

OpenGraphiti : Data Visualization Framework | #SNA #open #dataviz | e-Xploration | Scoop.it
luiy's insight:
Description

OpenGraphiti is a free and open source 3D data visualization engine for data scientists to visualize semantic networks and to work with them. It offers an easy-to-use API with several associated libraries to create custom-made datasets. It leverages the power of GPUs to process and explore the data and sits on a homemade 3D engine.

 

YOUTUBE: https://www.youtube.com/watch?v=TE9qsYBu8MM

 

 

 

 

 

 

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Visualizing The Explosive Growth Of The #Robotics Industry | #SNA #dataviz

Visualizing The Explosive Growth Of The #Robotics Industry | #SNA #dataviz | e-Xploration | Scoop.it
Meet the overlords of your new overlords.
luiy's insight:

Over the past several years, a new wave of robot technology has offered us a glimpse at our heavily automated future, featuring drones, telepresence bots, therapeutic robots, and surgery bots that assist (or maybe take over for) doctors. The robotics industry has actually been around for a long time, with numerous companies working on warehouse automation, industrial robotics, and the like since the middle of the last century.

 

But as this interactive visualization from the Boston Consulting Group (BCG) and Quid reveals, the industry is expanding at near-warp speed.

 

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#Violence and guns in best-selling #videogames | #dataviz #opendata

#Violence and guns in best-selling #videogames | #dataviz #opendata | e-Xploration | Scoop.it
Research into connections between gun violence and video games to violence in real life has been inconclusive. As the hype for the latest in the Grand Theft Auto series builds up, a Guardian analysis of the top 50 video games sold in 2012 found more than half contain violent content labels, as assigned by an independent video game rating board (ESRB). Overall, one-third have weapons that depict real-life firearms
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