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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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Rescooped by Ashish Umre from Influence et contagion
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#Stigmergic dimensions of Online Creative Interaction | #algorithms #memes

#Stigmergic dimensions of Online Creative Interaction | #algorithms #memes | Social Foraging | 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. The Picbreeder applet starts by randomly generating several images, which are then mated and mutated based on the user’s selections. The user can then publish the image to the Picbreeder website where other users can download and continue the image’s evolution. Within this process, users collaboratively create imageswith significant complexity, all without explicit communication. In short, Picbreeder encourages a new form of stigmergic collaborative creation. The most surprising result of the Picbreeder experiment during more than 3 years of operation has been the quality of the  resulting images, despite the limited ways of interacting with other users. This fact challenges some commonly held notions of creativity, both online and offline. While current cognitive research in creativity places significant emphasis of the personal traits and cognitive structures that give rise to creative thought, Picbreeder highlights the potential for the emergence of creativity through stigmergic interaction. Picbreeder offers a rich data set for analysis of collaborative interaction with over 155,000 inputs from hundreds of users combined to create over 7500 images. It is hoped that the insights offered in this paper will influence both the understanding of collaborative creativity and the development of new modes of online creative interaction.


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luiy's curator insight, May 2, 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

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How to Burst the "Filter Bubble" that Protects Us from Opposing Views

How to Burst the "Filter Bubble" that Protects Us from Opposing Views | Social Foraging | 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.

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luiy's curator insight, April 11, 1:19 PM

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.

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Algorithm Distinguishes Memes from Ordinary Information

Algorithm Distinguishes Memes from Ordinary Information | Social Foraging | Scoop.it
Network theorists have developed a way to identify the top memes in science and study how they evolved 

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luiy's curator insight, May 26, 5:04 AM

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.

  

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


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