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Comparing Facebook EdgeRank and Google PageRank

http://techcrunch.com/2010/04/22/facebook-edgerank/

This article explains how Facebook’s EdgeRank formula chooses what content is displayed on a user’s news feed. Although their contexts are quite different, Facebook EdgeRank and Google PageRank have similar purposes and methods.

Google’s PageRank algorithm is able to produce a relevant list of web pages for a given user’s search within fractions of a second. Google found success because it was able to sift through the overwhelming number of websites on the internet and provide users with something useful. Similarly, users of Facebook often have hundreds of “friends”, representing relationships with varying degrees of closeness. Without any way to filter updates, posts, and interactions, Facebook could easily become overwhelming and useless, cluttered with information a given user doesn’t care about. To avoid this problem, Facebook introduced EdgeRank, an algorithm that chooses relevant content to be posted on a user’s news feed. Both algorithms distill a large interconnected network into a manageable list of information, customized for each user.

The method for calculating this list is surprisingly similar for both algorithms, despite their different settings. EdgeRank determines whether or not an object appears on a person’s news feed by calculating three different components. The affinity score is related to the relationship between two users, based upon messages, profile views, and other types of interaction. Next, there is a weight given to the edge type in question; for example, a comment has a different weight than a “like”. The last component is a time delay; older edges have less importance. The object is then given a score and appears (or doesn’t appear) on a person’s news feed accordingly. This is similar to PageRank because the algorithm is based upon connections within the network. PageRank determines importance of a given page by calculating how much score it receives from other pages linking in to it. The algorithm does not care what the node itself is, but about the connections the node has. EdgeRank does consider what type of edge it is, but not the specific information within the edge. In both cases, importance is based primarily upon endorsement instead of content.

The internet is significantly more manageable for everyday users because Google and Facebook are able to analyze the network and organize the information within it. Both the EdgeRank and PageRank are able to do this by examining connections within the network structure, avoiding the impossible task of probing the content within the nodes of the network.

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One Response to “ Comparing Facebook EdgeRank and Google PageRank ”

  • Google Plus Followers

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