http://www.shmula.com/197/digg-as-a-game

In this article, the author analyzes why and how users artificially inflate their digg scores on articles. Digg, for those not familiar with it, is a site that people join and post articles, pictures or videos that they found interesting and the other members of the digg community vote on whether or not the article was interesting. The main problem they discuss is that there are a few users or user groups that have been continually pushing their articles into the most “digged” spots, they discuss the underlying economics of why a user tries to achieve relevant digg posts, and explores the information flow within a larger network (how a few well connected nodes can really influence the whole rest of the network). This article was very interesting as it showed a large number of amateur economists trying to apply many of the economic concepts they learned to discuss problem of hijacked ratings on digg. They debate on the Game Theory nature of posts, as well as Information Cascades and the power of a small set of well connected nodes in a larger network (ie network bridges).

The article discussed the basics of game theory, such as strategies, payoffs, information, and rationality, and the prisoner’s dilemma outcome which we discussed in class. While the game theory analysis was interesting, what more caught my attention was when they started talking about information cascades. “The Digg system of measuring a story’s importance is based on a semi-random set of people voting for or against a semi-random set of news stories.” So the factors at hand are a couple of networks, one for people and the other for news stories, and people trying to post relevant articles to gain esteem within the digg community. This article discusses without explicitly mentioning it how if a well connected node receives a piece of information, how it can effectively control its dissemination, which is graph theory. Also, as the topic becomes more relevant or gains more attention, there are Information Cascades, where users who usually wouldn’t be interested in a topic pick up articles because if many other people think it is relevant, they might have better information. It is quite interesting to see how complex human interaction is and also how relevant so many of the topics network theory are to being able to describe a seemingly unrelated problem.

PS I was going to post a different article that discussed another topic, but when I saw everyone else had been posting on Information Cascades, I decided to post on it as well. (Can someone say theory in action?)