Influence et contagion
6.7K views | +7 today
Follow
Influence et contagion
L'influence et la contagion dans la cyberculture
Curated by luiy
Your new post is loading...
Your new post is loading...
Scooped by luiy
Scoop.it!

Can #Ebola Be Stopped By Treating It Like A Terrorist Network? | #algorithms #health

Can #Ebola Be Stopped By Treating It Like A Terrorist Network? | #algorithms #health | Influence et contagion | Scoop.it
A Florida defense contractor is using the data mining tools of counterterrorism to take aim at Ebola.
luiy's insight:

Six months after its latest resurgence, the Ebola virus shows no signs of letting up. "We desperately need new strategies adapted to this reality," said Dr. Joanne Liu, international president ofDoctors Without Borders in a grim statement last week. One hope is that data, which can spread faster than disease, could give humans a technological leg up on the spread of the epidemic. The problem with this data is that it's massive and often unstructured.

 

Can scientists and medical professionals make sense of the mess in time for it to make a difference?

more...
No comment yet.
Scooped by luiy
Scoop.it!

#Google matrix analysis of directed networks | #datascience #algorithms

#Google matrix analysis of directed networks | #datascience #algorithms | Influence et contagion | Scoop.it
luiy's insight:

This review describes matrix tools and algorithms which facilitate classification and information retrieval from large networks recently created by human activity. The Google matrix formed by links of the network has typically a huge size. Thus, the analysis of its spectral properties including complex eigenvalues and eigenvec- tors represents a challenge for analytical and numerical methods. It is rather surprising, but the class of such matrices, belonging to the class of Markov chains and Perron-Frobenius operators, was practically not inves- tigated in physics. Indeed, usually the physical prob- lems belong to the class of Hermitian or unitary ma- trices. Their properties had been actively studied in the frame of Random Matrix Theory (RMT) (Akemann et al., 2011; Guhr et al., 1998; Mehta, 2004) and quantum chaos (Haake, 2010). The analytical and numerical tools developed in these research fields allowed to understand many universal and peculiar features of such matrices in the limit of large matrix size corresponding to many-body quantum systems (Guhr et al., 1998), quantum comput- ers (Shepelyansky , 2001) and a semiclassical limit of large quantum numbers in the regime of quantum chaos (Haake, 2010). In contrast to the Hermitian problem, the Google matrices of directed networks have complex eigenvalues. 

more...
No comment yet.
Scooped by luiy
Scoop.it!

Top 10 #algorithms in data mining | #datascience

luiy's insight:

This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. These top 10 algorithms are among the most influential data mining algorithms in the research community. With each algorithm, we provide a description of the algorithm, discuss the impact of the algorithm, and review current and further research on the algorithm. These 10 algorithms cover classification clustering, statistical learning, association analysis, and link mining, which are all among the most important topics in data mining research and development.

more...
No comment yet.
Rescooped by luiy from e-Xploration
Scoop.it!

#Stigmergic dimensions of Online Creative Interaction | #algorithms #memes

#Stigmergic dimensions of Online Creative Interaction | #algorithms #memes | Influence et contagion | Scoop.it
This paper examines the stigmergic dimensions of online interactive creativity through the lens of Picbreeder. Picbreeder is a web-based system for collaborative interactive evolution of images. Th...
more...
luiy's curator insight, May 2, 2014 2:56 PM

Creativity as stigmergy

 

If stigmergy happens when an agent’s effect on the environment “stimulates and guides” the work of others, then certainly creative communities must be subject to some kind of stigmergy. No creative endeavor exists in a vac- uum, and being inspired and stimulated by the work of another is so fundamental to creative communities of artists, academics, engineers, etc., that it is difficult to imagine these communities functioning any other way.

 

Closely related to the concept of stigmergy is the concept of self-organization. The reason that it is remarkable that one user’s work stimulates another’s is the emergence of patterns that appear as if that they could be centrally controlled. Often, a mix of direct communication and con- trol as well as emergent properties of the social structure give rise to collaborative creative activities. Fig. 4 suggests an informal ordering of the amount direct communication and coordination involved in several different types of creative processes, with emergent creative processes on the left end, and highly coordinated processes on the right

Scooped by luiy
Scoop.it!

News Information Flow Tracking, Yay! (NIFTY) : System for large scale real-time tracking of #memes | #datascience #algorithms

more...
No comment yet.
Scooped by luiy
Scoop.it!

Twitter Trends Help Researchers Forecast Viral #Memes | #SNA #contagion

Twitter Trends Help Researchers Forecast Viral #Memes | #SNA #contagion | Influence et contagion | Scoop.it
Researchers are forecasting which memes will spread far and wide
luiy's insight:

What makes a meme— an idea, a phrase, an image—go viral? For starters, the meme must have broad appeal, so it can spread not just within communities of like-minded individuals but can leap from one community to the next. Researchers, by mining public Twitter data, have found that a meme's “virality” is often evident from the start. After only a few dozen tweets, a typical viral meme (as defined by tweets using a given hashtag) will already have caught on in numerous communities of Twitter users. In contrast, a meme destined to peter out will resonate in fewer groups.

 

“We didn't expect to see that the viral memes were going to behave very differently from nonviral memes at their beginnings,” says Lilian Weng, a graduate student in informatics at Indiana University Bloomington. Those differences allowed Weng and her colleagues to forecast memes that would go viral with an accuracy of better than 60 percent, the team reported in a 2013 study.

more...
No comment yet.
Scooped by luiy
Scoop.it!

graph-tool: Efficent network analysis with #python | #SNA #tools

graph-tool: Efficent network analysis with #python | #SNA #tools | Influence et contagion | Scoop.it
graph-tool: Efficent network analysis with python
luiy's insight:

An extensive array of features is included, such as support for arbitrary vertex, edge or graph properties, efficient "on the fly" filtering of vertices and edges, powerful graph I/O using the GraphML, GML and dot file formats, graph pickling, graph statistics (degree/property histogram, vertex correlations, average shortest distance, etc.), centrality measures, standard topological algorithms (isomorphism, minimum spanning tree, connected components, dominator tree, maximum flow, etc.), generation of random graphs with arbitrary degrees and correlations, detection of modules and communities via statistical inference ,,,,,, 

more...
No comment yet.
Scooped by luiy
Scoop.it!

#Algorithm Distinguishes #Memes from Ordinary Information | #contagion

#Algorithm Distinguishes #Memes from Ordinary Information | #contagion | Influence et contagion | Scoop.it
Network theorists have developed a way to identify the top memes in science and study how they evolved 
luiy's insight:

Memes are the cultural equivalent of genes: units that transfer ideas or practices from one human to another by means of imitation. In recent years, network scientists have become increasingly interested in how memes spread.

This kind of work has led to important insights into the nature of news cycles, into information avalanches on social networks and into the role that networks themselves play in this spreading process.

 

But what exactly makes a meme and distinguishes it from other forms of information is not well understood. Today, Tobias Kuhn at ETH Zurich in Switzerland and a couple of pals say they’ve developed a way to automatically distinguish scientific memes from other forms of information for the first time. And they’ve used this technique to find the most important ideas in physics and how they’ve evolved in the last 100 years.

 

The word ‘meme’ was coined by the evolutionary biologists Richard Dawkins in his 1976 book The Selfish Gene. He argued that ideas, melodies, behaviours and so on, all evolve in the same way as genes, by means of replication and mutation, but using human culture rather than biology as the medium of evolution.

  

more...
No comment yet.
Scooped by luiy
Scoop.it!

How to Burst the "Filter Bubble" that Protects Us from Opposing Views | #algorithms #homophily

How to Burst the "Filter Bubble" that Protects Us from Opposing Views | #algorithms #homophily | Influence et contagion | Scoop.it
Computer scientists have discovered a way to number-crunch an individual’s own preferences to recommend content from others with opposing views. The goal? To burst the “filter bubble” that surrounds us with people we like and content that we agree with.
luiy's insight:

The term “filter bubble” entered the public domain back in 2011when the internet activist Eli Pariser coined it to refer to the way recommendation engines shield people from certain aspects of the real world.

 

Pariser used the example of two people who googled the term “BP”. One received links to investment news about BP while the other received links to the Deepwater Horizon oil spill, presumably as a result of some recommendation algorithm.

 

This is an insidious problem. Much social research shows that people prefer to receive information that they agree with instead of information that challenges their beliefs. This problem is compounded when social networks recommend content based on what users already like and on what people similar to them also like.

 

This is the filter bubble—being surrounded only by people you like and content that you agree with.

 

And the danger is that it can polarise populations creating potentially harmful divisions in society.

more...
No comment yet.
Scooped by luiy
Scoop.it!

How Gangnam Style" Went #Viral | #SNA #contagion #datascience

How Gangnam Style" Went #Viral | #SNA #contagion #datascience | Influence et contagion | Scoop.it
Data scientists trace how the most-viewed video in YouTube history spread across the Internet
luiy's insight:

When South Korean pop star Psy released his “Gangnam Style” video in 2012 it spread like wildfire. Researchers at Indiana University Bloomington tracked the spreading meme by following how Twitter users shared the video with friends and strangers alike. By the time 200 tweets had linked to the video among the subset of Twitter users studied, “Gangnam Style” had already reached 86 different communities of users (blue nodes). After 3,000 tweets the meme had spread to nearly 1,000 different communities (green). “Gangnam Style” soon became the most-viewed video in YouTube history; by late 2013, the video had amassed more than 1.8 billion views.

more...
No comment yet.