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Google and its Complexities

“We can think of PageRank as a kind of “fluid” that circulates through the network, passing from node to node across edges and pooling at the nodes that are most important.” (Textbook page 359).

It is no secret that the internet has grown to a massive web of millions of links to information and is constantly growing. Due to the fact that all internet users are also contributors, one user’s simply pressing one link can have a huge impact on someone else’s internet experience. When we consider that the internet is a source for looking up information like an encyclopedia, it’s no wonder why search engines like Yahoo!,, and Google have been developed to organize the different web pages and to assist users with their searching tasks.

Tools have now been developed so that we may compare the results of different search engines side by side:

Why would the results of two search engines be different? The search engines yield different results because they use different algorithms in order to determine which websites are most important and relevant to the searcher. We have discussed in class how Google uses PageRank in their algorithm in order to organize search results. By computing PageRank, Google can determine how connected a page is in terms of both incoming and outgoing links. The more connected a page is, the higher it’s PageRank. If a website only consists of many outgoing links, then its PageRank will be zero. This shows that PageRank depends on overall connectivity.

While part of Google’s algorithm uses PageRank to order its pages, they use many other factors as well:

Here, Google states that they “use more than 200 signals, including PageRank, to order websites, and we update these algorithms on a weekly basis. For example, we offer personalized search results based on your web history and location.”
With the development of Google+, people can now “hop on the bandwagon” and share certain sites or topics that they like with other users, similar to the Facebook “like” system. If we picture the internet as a web of nodes and edges between both pages and people looking at pages, PageRank only considers the number of incoming and outgoing connections between pages. However, Google adds more information to this picture, including strong/weak ties, positive/negative ties, proximity, and now, with Google+, whether your friends have strong/weak ties and positive/negative ties with pages. With all of this information, Google can have a more accurate number with which to rank pages in terms of relevance to the searcher.

Google+ seems to be becoming an incredibly useful tool for Google to collect information about their searchers’ preferences. They are now in the process of making a music application to determine a person’s musical preferences based on both their previous web searches, their friends’ music taste, and the number of people who are also connected to that song or artist.

While this sounds a lot like Apple’s “Music Genius,” it is more complex because it takes into account the ties that a user’s friends have, rather than merely information about their own musical preferences.

It is clear that Google has come a long way from just listing their results based on the PageRank. When we consider that the World Wide Web is not just a network of interlinked websites but also a network between people, the types of information available become both more complex and vast. Google has been taking advantage of the additional details to be gained from looking at the network in this way, and I’m sure that we can expect more personalized results in the future!


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