pagerank-algorithm

PageRank Algorithm

What is the PageRank algorithm?

• The PageRank algorithm is a crucial part of search ranking systems

• It was originally developed by Larry Page and Sergey Brin, the founders of Google

• Widely used: Many search engines, especially Google, rely on PageRank to help order search results

• Purpose: It evaluates and ranks web pages based on their perceived relevance and importance

• Impact: Pages that are considered more important (often because they are linked to by other high-quality pages) rank higher in search results

Why is the PageRank algorithm important?

• The PageRank algorithm was created to tackle the difficulty of determining the importance of web pages with the immense amount of information available

• The purpose of the algorithm is to provide better search results that are more precise and related by taking into account various factors beyond just matching keywords

Key elements of the PageRank algorithm

• There are 4 key elements to the PageRank algorithm:

  • Link analysis

  • Link weight distribution

  • Iterative calculation

  • Damping factor

Link analysis

• The PageRank algorithm analyses the structure of links between pages on the web

• Web pages are given importance by the algorithm, which considers the quantity and quality of inbound links from other pages

• Each link acts as a “vote” for the target page, with the voting weight determined by the importance of the linking page

• Websites that have more high-quality links pointing towards them are deemed to be more valuable and pertinent and have a higher weight

• Webpages with a higher weight will score more highly and have a higher ranking

Link weight distribution

• The importance of a webpage is calculated by PageRank, which takes into account the total number of “votes” it has received

• The algorithm distributes the importance of a page to the pages it links to by sharing a portion of its importance with each outgoing link

• By following this process, pages of superior quality are given greater importance and make a larger impact in determining the ranking of other pages

Iterative calculation

• The PageRank algorithm uses a repetitive calculation process. At the beginning, every webpage is given the same value to start with

• In subsequent iterations, the significance of each page is re-evaluated by considering the weighted impact of inbound links

• The process continues until the rankings become stable

Damping factor

• The damping factor is a value between 0 and 1 (usually 0.85)

• It represents the probability that a user will not follow a link on a page and will instead jump to a random new page

• It prevents the algorithm from getting stuck in infinite loops and makes the model more realistic

Factors influencing PageRank

Although the initial PageRank algorithm mainly concentrated on link analysis, present-day search engines consider many factors to improve search results rankings. These factors may include:

• Relevance

• User engagement

• Authority and trust

• Content freshness

• Mobile-friendliness

Relevance

• The content of a web page is a crucial factor in determining its ranking in search results. This is influenced by the keywords used, the quality of the content, and how relevant it is to the search query

User engagement

• The way users interact with a website can be measured through metrics like click-through rates, time spent on a page (dwell time), and bounce rates. These metrics can reveal the level of user engagement

• Pages that receive greater engagement from users may be deemed more valuable

Authority & trust

• The reputation and authority of a webpage or website play a crucial role

• Several factors can enhance a website’s ranking, including the age of the domain, quality backlinks from reputable sources e.g. government website or the BBC, and trustworthy content 

Content freshness

• Search engines value fresh and up-to-date content

• Search queries may give priority to web pages that are frequently updated or have up-to-date information

Mobile-friendliness

• As mobile devices became more prominent, search engines started to factor in the mobile compatibility of web pages when determining their ranking

• Google primarily uses the mobile version of a site’s content to rank pages from that site

• Having a responsive design and optimising the user experience on mobile devices can have a positive impact on a website’s rankings

Limitations & evolving nature

• Although the PageRank algorithm is important in search engine rankings, it is not the only factor that determines them

• Search engines use different algorithms and factors to guarantee that they provide varied, relevant, and top-quality search outcomes

• Over time, the details of the PageRank algorithm have undergone changes. Search engines regularly enhance their ranking methods to cater to new challenges and meet user expectations

How does PageRank work?

• To illustrate how PageRank works, let’s use players in a football match where:

  • Each player represents a page

  • Each pass between 2 players represents a link between 2 pages

PageRank Analogy – a team of football players

• The main things PageRank uses are:

  • The number of links the page gets (or the number of passes a player receives)

  • The importance of a page is determined by the number of links pointing towards it or by how frequently the player who passed the ball is passed to

• The PageRank of each player gets updated every time they receive the ball

• This continues throughout the game

PageRank Analogy – the players receive a numerical rating based on number and frequency of passes

• As more passes are made, the PageRank of each player undergoes changes

• As a result, the PageRank of every player they pass to will be altered

• The number represents each player’s PageRank – the higher the number, the better

• Once the game concludes, players can be ranked to determine the best performer

PageRank Analogy – the players can now be sorted by their rating