EdgeRank

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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 stopped 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:

where:

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]

Impact[edit]

EdgeRank and its successors have a broad impact on what users actually see out of what they ostensibly follow: for instance, the selection can produce a filter bubble (if users are exposed to updates which confirm their opinions etc.) or alter people's mood (if users are shown a disproportionate amount of positive or negative updates).[3]

As a result, for Facebook pages, the typical engagement rate is less than 1 % (or less than 0.1 % for the bigger ones)[4] and organic reach 10 % or less for most non-profits.[5]

As a consequence, for pages it may be nearly impossible to reach any significant audience without paying to promote their content.[6]

See also[edit]

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

References[edit]

  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.com. 2010-04-22. Retrieved 2012-12-08. 
  3. ^ Rushe, Dominic (2014-10-02). "Facebook sorry – almost – for secret psychological experiment on users". The Guardian. ISSN 0261-3077 – via The Guardian. 
  4. ^ "What is a good Facebook engagement rate? See numbers here". www.michaelleander.me. Retrieved 2016-12-17. 
  5. ^ "The 2016 Social Media Director's Guide to Benchmarks | M+R". www.mrss.com. Retrieved 2016-12-17. 
  6. ^ "Facebook Organic Reach Is DEAD (Here's What You Can Do About It)". hypebot. Retrieved 2016-12-17. 

External links[edit]