In an effort to measure the importance of links, some people began to experiment with alternative metrics. Anchor text contained hints needed by algorithms. These authors of PageRank used this idea to measure importance by examining which authoritative websites were passing authority to their pages by linking to them. By studying the usability of websites, they hoped to create a new way to rank search results. But that was before social media and other SEO metrics took hold.
PageRank is a ranking factor for Google
The original concept of PageRank was introduced in 1998 by Larry Page and Sergey Brin, and was a fundamental part of Google’s search engine. PageRank ranks pages based on the number and quality of links pointing to them. Today, the formula is still used by Google, but it has been updated to be more complex. Regardless of how complicated it is, the concept is still largely the same.
In 2004 Google updated the PageRank patent and introduced the idea that links may have varying values depending on their potential to be clicked. Links placed at the top of a page and those with long and informative anchor texts are likely to be clicked. Google also began considering the likelihood of clicks when serving rankings and assessing the authority of websites. But the concept of PageRank still persists today, as it does in most other search engine algorithms.
While the popularity of a web page can influence its ranking in the SERPs, the true relevance of a website depends on the content and links that are being shared on it. Google uses page categories and keywords in URLs as relevancy signals. Pages that have similar content to the one the surfer is searching for may also receive a relevancy boost. For example, a page that contains a recipe for carbonara may appear higher in the search results.
In the early days, the popularity of PageRank prompted an obsession with how websites rank. It inspired a number of SEOs to manipulate PageRank for their own websites. But the Google team realized that making PageRank public was adding little value to website owners. PageRank is still a major ranking factor for Google, and it is an integral part of the ranking formula. So, the real question is, how do you optimize for it?
It is a recursive algorithm
The Google search engine uses a recursive algorithm to determine a page’s PageRank. In essence, a page’s PageRank is the sum of the PageRanks of all the pages that link to it. Each link is weighted accordingly, meaning that a high PageRank page will have a higher PageRank than a low-ranking one. Because of this, Google introduced the Hilltop Algorithm in 2003, which is a recursive method of identifying authoritative and expert pages.
The PageRank algorithm produces a probability distribution representing how likely a person is to arrive at a particular page. Generally, it can be applied to collections of any size. In general, PageRank computations require several passes through a collection, adjusting the approximate PageRank values as it goes along. The recursive algorithm calls itself with smaller inputs after it solves the current ones.
It is based on links to a website
Ahrefs UR is an URL rating system inspired by Google’s PageRank. It is comparable to Moz’s PageRank and passes through the doFollow links on every page. The more links a site has, the higher its UR. Other metrics that measure website popularity are Ahrefs CF, Ahrefs CA, and Moz’s PA.
Alternative metrics to PageRank
PageRank was the first authority metric on the Web, and it still influences Google’s ranking signals today, though how they do so is not entirely clear. As such, relevant links from high-quality sources are a key factor in establishing authority and ranking well in Google’s search results. There are several alternative metrics for SEO, most of which focus on backlink quality and quantity. For example, Amazon Alexa Rank evaluates traffic to a website, and the quality parameters focus on the backlink profile.
As an example, Matteo Pasquinelli suggests that PageRank converges to a tolerable level in 52 iterations for a network of 322 million links, but it takes about 45 iterations for a network half that size to achieve this level of accuracy. Similarly, Katja Mayer proposes an alternative metric that accounts for the social component of the ranking system. While this is a complex concept, it is important to note that many researchers consider PageRank as a useful tool to foster thinking and debate.
Another popular alternative to PageRank is MozRank. It is an algorithm that tracks the number and quality of links that point to a page. The more high-quality links, the more authoritative the webpage is. This system was developed by Larry Page and Sergey Brin at Stanford University. In addition to linking quality, PageRank is based on a complex algorithm. The more inbound links a page has, the higher its PageRank score.
Another metric that relies on link authority is Trust Flow. Trust Flow increases when popular websites link to a page. But, it will always score lower than Citation Flow. Another option is Domain Rating, developed by Ahrefs, and is based on logarithmic scale from 0 to 100. It calculates the authority of entire websites and individual pages. PageRank is a popular algorithm used by Google to determine the credibility of websites.
