Google Hacks, 2nd Edition

Get Inside the PageRank Algorithm

Delve into the inner workings of the Google PageRank algorithm and how it affects results.

PageRank is the algorithm used by the Google search engine, originally formulated by Sergey Brin and Larry Page in their paper “The Anatomy of a Large-Scale Hypertextual Web Search Engine.”

It is based on the premise, prevalent in the world of academia, that the importance of a research paper can be judged by the number of citations the paper has from other research papers. Brin and Page have simply transferred this premise to its Web equivalent: the importance of a web page can be judged by the number of hyperlinks pointing to it from other web pages.

So What Is the Algorithm?

It may look daunting to non-mathematicians, but the PageRank algorithm is in fact elegantly simple and is calculated as follows:

PR(A) = (1-d) + d { PR(T1) + ... + PR(Tn) }
                    ------         ------  
                     C(T1)          C(Tn)

• PR(A) is the PageRank of a page A.

• PR(T1) is the PageRank of a page T1.

• C(T1) is the number of outgoing links from the page T1.

• d is a damping factor in the range 0 < d < 1, usually set to 0.85.

The PageRank of a web page is therefore calculated as a sum of the PageRanks of all pages linking to it (its incoming links), divided by the number of links on each of those pages (its outgoing links).

And What Does This Mean?

From a search engine marketer’s point of view, this means there are two ways in which PageRank can affect the position of your page on Google:

• The number of incoming links. Obviously, ...