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EdgeRank is the name commonly given to the algorithm that Facebook uses to determine what articles should be displayed in a user's News Feed. As of 2011, Facebook has switched from using the EdgeRank system and uses a machine learning algorithm that, as of 2013, takes more than 100,000 factors into account.[1]

EdgeRank was developed and implemented by Serkan Piantino.

Formula and factors[edit]

In 2010, a simplified version of the EdgeRank algorithm was presented as:


is user affinity.
is how the content is weighted.
is a time-based decay parameter.
  • User Affinity: The User Affinity part of the algorithm in Facebook's EdgeRank looks at the relationship and proximity of the user and the content (post/status update).[1]
  • Content Weight: What action was taken by the user on the content.[1]
  • Time-Based Decay Parameter: New or old. Newer posts tend to hold a higher place than older posts.[1]

Some of the methods that Facebook uses to adjust the parameters are proprietary and not available to the public.[2]

See also[edit]

  • PageRank, the ranking algorithm used by Google's search engine


  1. ^ a b c d McGee, Matt (Aug 16, 2013). "EdgeRank Is Dead: Facebook's News Feed Algorithm Now Has Close To 100K Weight Factors". Retrieved 28 May 2014. 
  2. ^ "EdgeRank: The Secret Sauce That Makes Facebook's News Feed Tick". Techcrunch. 2010-04-22. Retrieved 2012-12-08.  External link in |publisher= (help)

External links[edit]