PageRank Algorithm

PageRank (PR) is a groundbreaking algorithm developed by Google founders Larry Page and Sergey Brin that measures the importance of web pages based on the quality and quantity of links pointing to them 1. The algorithm, which gets its name from both the term "web page" and co-founder Larry Page, operates on the principle that more important websites are likely to receive more links from other websites 1.

How PageRank Works

The fundamental concept behind PageRank is treating links as votes of confidence between web pages infolab.stanford.edu. When one page links to another, it's essentially casting a vote for that page's importance. However, not all votes carry equal weight 2. The algorithm considers two key factors:

1. Link Quality: Links from high-authority pages (those with higher PageRank) carry more weight than links from less important pages 3
2. Link Distribution: The value of each link is divided by the total number of outgoing links on the page. This means a link from a page with few outbound links is worth more than one from a page with many links 2

Mathematical Foundation

The PageRank calculation uses a probability distribution model that determines how likely a person randomly clicking links would land on any given page 3. The original formula can be expressed as:

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

Where:

• PR(A) is the PageRank of page A
• d is the damping factor (typically 0.85)
• PR(Tn) is the PageRank of pages linking to page A
• C(Tn) is the number of outbound links from those pages

Evolution of PageRank

The algorithm has undergone significant evolution since its inception:

1. 1998: First PageRank patent filed patents.google.com
2. 2000: Google Toolbar launched, making PageRank scores visible to the public googlepress.blogspot.com
3. 2005: Introduction of nofollow attribute to combat comment spam googleblog.blogspot.com
4. 2016: Google removed public PageRank scores searchengineland.com

Modern Implementation

While PageRank is no longer publicly visible, it remains an important part of Google's ranking algorithm 2. The modern version has evolved to include:

1. Reasonable Surfer Model: Not all links on a page are valued equally patents.google.com
2. Quality Signals: Integration with other ranking factors like E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) 3
3. Spam Prevention: Advanced algorithms to detect and devalue artificial link schemes developers.google.com

Impact on SEO

While PageRank scores are no longer public, the principles behind the algorithm remain crucial for SEO:

1. Link Quality: Focus on earning links from reputable, relevant websites 2
2. Content Authority: Create valuable content that naturally attracts high-quality backlinks 9
3. Internal Linking: Maintain a logical site structure that efficiently distributes PageRank throughout your website 16

Google's Current Stance

Google has confirmed that PageRank continues to be one of hundreds of ranking signals used today. In 2017, Google's Gary Illyes stated:

Loading… DYK that after 18 years we're still using PageRank (and 100s of other signals) in ranking?

This confirmation demonstrates that while PageRank has evolved, it remains a fundamental part of Google's search algorithm 2.

Related Links:

• patents.google.com
• developers.google.com
• searchenginejournal.com
• twitter.com