A Guide to Understanding Google’s PageRank Algorithm

PageRank was introduced by Google in 1998 and named after Google's co-founder, Larry Page. This algorithm was used by Google to assign a numerical ranking to web pages based on the internal links present within a website. It was the first ranking algorithm developed by Google for ranking web pages.

Nowadays, there are many more algorithms that determine the ranking of web pages. According to Google, they no longer use this algorithm for ranking web pages but it is a fundamental concept in SEO. In this article, I will guide you through the PageRank algorithm.

Algorithm

An algorithm is a step-by-step procedure for solving a problem. It consists of a set of instructions that lead to the solution of a problem in an optimized way. Algorithms can be implemented in various fields, including computer science, mathematics, and everyday tasks. Here, we are going to discuss one of the computer science algorithms developed by Google.

Types of Links

There are three primary types of links: inbound links, outbound links, and dangling links, each serving a unique purpose in the web's link structure.

• Inbound links : All the incoming links to a webpage are called inbound links. Let's assume we have three pages: A, B, and C. If there is a link on page B that redirects to page A and another link on page C that also redirects to page A, then the total number of links redirecting to page A is two (from page B and page C). So, the inbound links to page A are two.

• Outbound links : All the outgoing links from a webpage are outbound links. Let's assume we have three pages: A, B, and C. If there is a link on page A that redirects to page B, then the total number of outgoing links on page A is one (to page B). So, the outbound link count for page A is one.

• Dangling links : Dangling links are web pages that have inbound links but no outbound links. Let's assume there are three pages: A, B, and C. If there is a link on page A that redirects to page B and a link on page C that also redirects to page B, but there are no links on page B that redirect to pages A or C, then page B has two inbound links and zero outbound links. These are called dangling links.

How PageRank Algorithm works ?

PageRanks is calculated by special algorithm by giving the numerical weight to the web page which is based on how likely a link is to be clicked.

The complete PageRank formula used by Google to measure the importance of web pages based on the links between them. It is defined as follows:

Here's a breakdown of the formula:

• PR(u) : PageRank of page u

• d: Damping factor (usually set to 0.85)

• N: Total number of pages

• M(u) : Set of pages that link to page u or inbound links

• PR(v) : PageRank of page v

• L(v) : Number of outbound links on page v

Explanation

1. Damping Factor (d): This factor represents the probability that a user will continue clicking on links. It accounts for the likelihood that a user will stop clicking after following a few links. The standard value for d is 0.85, meaning there is an 85% chance that the user will follow a link, and a 15% chance that they will stop clicking and jump to a random page.

2. Random Jump Factor (1−d/N): This part of the formula accounts for the probability of jumping to a random page. (1−d)/N distributes this probability uniformly across all pages.

3. Summation (∑(v∈M(u)) PR(v)/L(v)): This part calculates the contribution to the PageRank of page u from all pages v that link to u. Each page v's PageRank is divided by its number of outbound links L(v), distributing v's PageRank proportionally to all the pages it links to.

Summary

PageRank, introduced by Google in 1998 and named after co-founder Larry Page, is an algorithm used to assign numerical rankings to web pages based on their internal links. Though Google no longer uses it, PageRank remains a fundamental concept in SEO. This article explains the PageRank algorithm, including types of links and how the calculation works, incorporating factors like damping and random jumps to measure the importance of web pages based on linking patterns.