Have you ever wondered how Google knows which search results to show you when you research something? Have you wondered how Facebook suggests people you may know and may want to send a friend request to? Google, Facebook and many other websites use link analysis and page rank to do this. Link analysis is a computational concept widely used by search engines and social media as a means to form connections and link what we do on the internet to other things we may do on our computational devices. Link analysis is very prevalent in such things as internet cookies in which ads from websites that you may have visited often show up on the side bars of your computer because it remembers that you visited that website and links your computer to the website. It is also prevalent, for example, on Facebook when you see mutual friends as possible people to add. Link analysis looks at your current friends and your personal settings (such as which university you went to or the area you live in) and finds a link between you and other people that have that friend or other aspects in your profile in common.
Link analysis can be described as being a graph in a matrix. The structure of the graph in the matrix can help the computer assess the importance of each node and essentially whether or not it would be relevant if it were presented to the user. The mathematics behind link analysis can be very extensive and confusing therefore the picture below shows the concept of link analysis in a non computational way to help visualize what it actually is in simpler terms.
Link analysis is also related to page rank in search engines. Link analysis allows the search engine to remember what you and other people have searched regarding a certain topic and rank it in a way that makes the most related, and also most visited, page of the topic show up at the top of your search. Google and most search engines use the concept portrayed in the diagram below in their page ranks. Page ranks are easiest to explain using examples therefore page C and page E will be used as examples. Page C has less links to it than page E yet page C has a higher percentage chance of being visited because the few links to page C are deemed more important than the many links to page E. This may be because page C was determined to be more related to the topic searched even though there are less links to it. Therefore the number of links to a page does not automatically mean that it is going to be ranked the highest as content quality also matters.
Link analysis and Page Rank are very helpful sources that we use in our day-to-day lives that make researching and finding new friends to add much easier. If you would like even more clarification or elaboration on these topics please look at my references they are very helpful!
References:
https://en.wikipedia.org/wiki/PageRank#History
http://pr.efactory.de/e-pagerank-algorithm.shtml
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