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The ultimate goal: a truly computational understanding of human society, say Yahoo’s computational anthropologists. Via luiy 
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luiy's curator insight,
May 1, 2014 8:37 PM
Resuming from last time, I've made some updates to the philosophers' social network including publishing two interactive maps. Quick introduction: you know that sidebar on wikipedia where it tells you someone was influenced by someone else, linking to them? These graphs are generated from asking wikipedia for a comprehensive list of every philosopher's influence on every other. There are some sample-bias issues and data problems I went over in the first part of the series, but overall it's both beautiful and interesting.
Interactive visuals
The first lets you zoom dynamically and makes it easier to see local networks. When you hover over individual philosophers, those who are not linked to them or from them disappear. This uses a tool called sigma.js.
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Within its limits, SNA can be applied to identify individuals or organizations within a network, generate new leads and simulate flows of information or money throughout a network. Via luiy
luiy's curator insight,
January 17, 2014 8:53 AM
Social Network Analysis, as an analytic method, has inarguable applicability to the field of intelligence and is progressively reshaping the analytic landscape in terms of how analysts understand networks. For example, analysts currently use SNA to identify key people in an organization or social network, develop a strategic agent network, identify new agents and simulate information flows through a network. Beyond this, SNA can be easily combined with other analytic practices such as Geographic Information Systems (GIS), gravity model analysis or Intelligence Preparation of the Battlefield (IPB) to create robust, predictive analyses. |
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These cluster maps give us a two-dimensional look at the complex arguments Americans posted on the topic of net neutrality. One theme in the comments had to do with the American dream. Via luiy
luiy's curator insight,
August 19, 2014 5:32 PM
How To Read This Cluster Map
- Similar nodes typically cluster together and clusters are grouped by color - Each node represents a news story; a node sized by degree represents number of connections (i.e., similarity) to other nodes - Connections represent similar language used across nodes - A node bridging two clusters can indicate a story that synthesizes multiple topics
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PLOS ONE: an inclusive, peer-reviewed, open-access resource from the PUBLIC LIBRARY OF SCIENCE. Reports of well-performed scientific studies from all disciplines freely available to the whole world. Via Bryan A. Knowles, luiy
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Today, Luca Maria Aiello at Yahoo Labs in Barcelona, Spain, and a couple of pals, change that. They tease apart the nature of the links that form on social networks and say these atoms fall into three different categories. They also show how to extract this information automatically and then characterize the relationships according to the combination of atoms that exist between individuals. Their ultimate goal: to turn anthropology into a full-blooded subdiscipline of computer science.
Aiello and co used two data sets from a pair of large social networks. The first consists of over 1 million messages sent between 500,000 pairs of users of the aNobii social network, which people use to talk about books they have read. The second is a set of 100,000 anonymized user pairs who commented on each other’s photos on Flickr, sending around 2 million messages in total.
The team analyzes these messages based on the type of information they convey, which they divide into three groups. The first type of information is related to social status; messages displaying appreciation or announcing the creation of the social tie such as a follow or like. For example, a user might say a photograph is “an excellent shot” or say they’ve followed somebody or acknowledged attention they’ve got by thanking them for visiting a site.
Alex Pentland would call this Social Physics.