Damn, Science Ruins Everything

I have always wondered at the sheer disdain people have for a story after a few days. Why do people tend to discard a story (like the Mumbai blasts which are already off a lot of front pages) even though it is a continuing saga.

Apparently so did statisticians at the University of Notre Dame in the US.

Albert-László Barabási of the University of Notre Dame in the US and colleagues in Hungary have calculated that the number of people who read news stories on the web decays with time in a power law, and not exponentially as commonly thought. Most news becomes old hat within a day and a half of being posted — a finding that could help website designers or people trying to understand how information gets transferred in biological cells and social networks

Talk about complexity!!

Their model reveals that a typical news site has a relatively stable “skeleton” — corresponding to the overall organization of the site — along with nodes (that is, actual stories) that are only temporarily linked to the main structure before being deleted from the site or not linked any more. In this sense, the network resembles a biological cell’s regulatory network, whose “wiring” can change rapidly during a cell cycle. It is also a bit like social networks: we each have a relatively stable core network of friends and acquaintances but the number of people we interact with can vary drastically from one day to the next.

To get a fuller understanding of such networks, Barabási and colleagues decided to study the visiting patterns on a popular Hungarian news and entertainment portal (origo.hu). Thanks to automatically assigned “cookies”, the scientists were able to reconstruct the browsing history of about 250,000 visitors to the site over the course of a month.

Question : Did they have permission from the 250,000 users on being lab rats? If not, what are the legal ramifications? Oh fuck, who cares, this is so interesting!!

The researchers found that the documents belonging to the skeleton of the website receive an approximately constant stream of visitors, which means that the cumulative number of visitors accessing these documents increases linearly in time. In contrast, the news documents receive the most hits directly after their release, and decrease with time. Thus, the cumulative numbers of visits here reach saturation after just a few days.

Barabasi’s team calculated the “half-life” of a news document, which corresponds to the period in which half of all visitors that eventually access it have visited. The researchers found that the overall half-life distribution follows a power law, which indicates that most news items have a very short lifetime, although a few continue to be accessed well beyond this period. The average half-life of a news item is just 36 hours, or one and a half days after it is released. While this is short, it is longer than predicted by simple exponential models, which assume that web page browsing is less random than it actually is.

So this post is relevant for exactly 36 hours. Oh well, at least I didn’t have to write this article. Long live copy-paste.

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