Google Pagerank Algorithm Has More Than One Use

The New York Times produces an annual list of the year’s best ideas. This year’s, “The Ninth Annual Year in Ideas,” included a study that used Google’s Pagerank Algorithm to create an extinction model. The purpose of the study was to build a model that would measure how much the extinction of a species would affect other animals whose survival depends greatly on this species. Everyone has heard of terms like the “food chain” or “the circle of life” and this was exactly what the two scientists were wanting to record and measure.

Google’s Pagerank Algorithm selects the most important websites or web pages to display in search engine results relating to a relevant topic that is queried by a user. Google determines this by sending crawlers to a site and indexing the information and computing its relevancy. Search engine optimizers have to make sure they have optimized their site well enough to be considered number one or ranked high in search engine results to give a website higher visibility, steady growth in traffic, better leads and a better conversion rate.

Other than having a highly relevant page, a large part of getting ranked on the top of Google is having a page that has in-links from other sites. This is why link building is very important for page rank. When your in-links are coming from high page rank sites, it benefits your page and it will grow in popularity itself, helping the web page survive in a sense.

The scientists used the formula in Google’s Pagerank Algorithm and were able to apply it to animals and how they relate to each other in the food chain. Instead of measuring importance of sites that interlink on the internet, they are measuring the importance of animals that interlink in an ecosystem.

“The world features countless interconnected systems ranging in size from the minuscule (metabolic networks within a single cell) to the immense (international financial markets). After publishing the paper, Stefano Allesina, of the University of Chicago, received e-mail messages from dozens of researchers interested in adapting the PageRank algorithm. “PageRank is a technique for finding hidden flows in huge quantities of data,” says Yonatan Zunger, a Google software engineer who used to work on search technology and who contacted Allesina after seeing his research. “There are all kinds of networks. PageRank is enormously applicable beyond the Web.”

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