Tomorrow is Today

Social Network Analysis of The Iliad and The Odyssey Indicates that They Were Likely Based on Real Events

Today, P J Miranda at the Federal Technological University of Paraná in Brazil and a couple of pals study the social network between characters in Homer’s ancient Greek poem, the Odyssey.

Their conclusion is that this social network bears remarkable similarities to Facebook, Twitter and the like and that this may offer an important clue about the origin of this ancient story.

Miranda and co think of each character in the Odyssey as a node in the network. They say a link exists between two characters when they meet in the story, when they speak directly to each other, cite one another to a third character or when it is otherwise clear that they know each other.

In analysing the Odyssey, they identified 342 unique characters and over 1700 relations between them. Having constructed the social network, Miranda and co then examined its structure.

“Odyssey’s social network is small world, highly clustered, slightly hierarchical and resilient to random attacks,” they say. What’s interesting about this conclusion is that these same characteristics all crop up in social networks in the real world. Miranda and co say this is good evidence that the Odyssey is based, at least in part, on a real social network and so must be a mixture of myth and fact.

(via The Remarkable Properties of Mythological Social Networks | MIT Technology Review)

Algorithm Mines Contact Data to Build Map of Social Relationships, Even Hidden Ones

…The ability to automatically create circles from a user’s contacts list is certainly valuable, The algorithm also has the ability to add new contacts to appropriate circles.

An important limitation, however, is the scalability of the approach. McAuley and Leskovec admit their algorithm is not particularly efficient, taking about an hour to identify ten circles from a list of 1000 Facebook contacts. That’s a lot of hours of processing for Facebook’s 1 billion users. However, they say that the technique should be quicker as broader patterns become clear once all users contacts have been taken into account.

For example, it may be possible to identify the set of all people on Facebook who went to a particular university. Then one person’s circle might consist of the intersection between this set and their contact list. Just how much of a speed up this would allow isn’t clear though.

Another important question for the future is how well in principle automatically-generated circles can be made to match ground truth circles, using only the information available in contact profiles and so on. It may be that many circles are created using information that users do not explicitly make available on social networks, such as a circle of ‘best friends’. If that’s the case, then these algorithms will never be able to reconstruct the ground truth circles perfectly. But perhaps this doesn’t matter if they provide a reasonable approximation to ground truth circles that users can tinker with at their leisure.

Another interesting approach is to look for patterns of links between contacts that users do not turn into circles—in other words connections between people that users have not recognised or want to keep hidden. Such a pattern might be linked with criminal activity, for example, or point to marketing information that could be sold.

(via Algorithm Predicts Circles of Friends Using Contacts Data | MIT Technology Review)

Big Data vs. The Zetas: Law Enforcement Using Social Network Analysis To Improve Anti-Cartel Strategy

Complexity analysis depicts drugs cartels as a complex network with each member as a node and their interactions as lines between them. Algorithms compute the strength and importance of the connections.

At first glance, taking out a central “hub” seems like a good idea. When Colombian drug lord Pablo Escobar was killed in 1993, for example, the Medellin cartel he was in charge of fell apart. But like a hydra, chopping off the head only caused the cartel to splinter into smaller networks. By 1996, 300 “baby cartels” had sprung up in Colombia, says Michael Lawrence of the Waterloo Institute for Complexity and Innovation in Canada, and they are still powerful today.

Mexican officials are currently copying the top-down approach, says Lawrence, but he doubts it will work. “Network theory tells us how tenuous the current policy is,” he says.

Now Colombian prosecutors have a new tool to add to their investigation methods: network analysis. This can be an integral part of the modern war on drugs, says Eduardo Salcedo-Albaran, director of the Vortex Foundation based in Bogotá.

Vortex uses network-analysis algorithms to construct diagrams for court cases that show the interactions between cartel members, governors and law enforcers.

These reveal links that are not otherwise visible, what Salcedo-Albaran calls “betweeners” - people who are not well-connected, but serve as a bridge linking two groups. In Mexico and Colombia, these are often police or governors who are paid by the cartels. “The betweener is the guy who connects the illegal with the legal,” says Salcedo-Albaran. Because many cartels depend on their close ties with the law to operate successfully, removing the betweeners could devastate their operations.

(via Destroying drug cartels, the mathematical way - physics-math - 17 October 2012 - New Scientist)

New Recommendations Model Treats Preferences Like an Infectious Disease

there is plenty of evidence that preferences are contagious. That means they can flow through social networks in the same way as epidemics spread.

So an alternative way to make recommendations is to look at the structure of an individual’s social network and predict how certain preferences are likely to spread through it. In the past, the factor that has limited the success of this type of prediction is a detailed knowledge of the structure of the network. But all that has changed in recent years with the huge popularity of online social networks. It’s now straightforward to see how individuals are linked.

Shang and co’s basic assumption is that if Adam likes a film, that preference will spread to his nearest neighbours on his social network—his friends—with a certain probability. If enough people share this preference, it can cascade through the network like a does of flu. So one way to predict that Eve will like this film is to see how close she is to Adam and how likely this preference will reach her. If Adam and Eve are close friends, this may be a relatively high probability.

(via Computer Scientists Exploit Social Networks To Create New Recommendation System - Technology Review)

A Network Model for Societal Evolution

Networks and complexity. Organizations and societies evolved from tribes to institutions to markets to networks, each stage triggered by major societal changes in communications. The written word enabled institutions, the printed word fostered regional and global markets, and the digital word is empowering worldwide networks.

(Via ibmsocialbiz)

Study of MMORPG Confirms Conventional Wisdom on How Men and Women Manage Social Networks

Szell and Thurner say the data reveals clear and significant differences between men and women in Pardus.

For example, men and women interact with the opposite sex differently. “Males reciprocate friendship requests from females faster than vice versa and hesitate to reciprocate hostile actions of females,” say Szell and Thurner.

Women are also significantly more risk averse than men as measured by the amount of fighting they engage in and their likelihood of dying. They are also more likely to be friends with each other than men.

These results are more or less as expected. More surprising is the finding that women tend to be more wealthy than men, probably because they engage more in economic than destructive behaviour.

“These results confirm quantitatively that females and males manage their social networks drastically different,” say Szell and Thurner.

Of course, there are important questions over the extent these findings reflect gender differences in the real world. One obvious problem is that of gender swapping: men who play as women and vice versa. Szell and Thurner say that other studies have shown that around ten per cent of online gaming populations engage in gender swapping. They say there’s no reason to think this would be any different in Pardus and that it shouldn’t effect the results.

A more serious problem could be the well known phenomenon that women tend to receive better treatment in male-dominated online gaming communities. Indeed, Szell and Thurner say they can see evidence of this in their data. That’s something they’ll need to look into in more detail.

There s one group for whom this kind of study will be invaluable: advertisers and marketeers. That makes it potentially valuable form a commercial point of view.

(via How Men and Women Manage Their Social Networks Differently - Technology Review)

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