EdgeRank
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
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]
See also
- PageRank, the ranking algorithm used by Google's search engine
References
- 1 2 3 4 McGee, Matt (Aug 16, 2013). "EdgeRank Is Dead: Facebook's News Feed Algorithm Now Has Close To 100K Weight Factors". Retrieved 28 May 2014.
- ↑ "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
This article is issued from Wikipedia - version of the 6/9/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.