EdgeRank was the original algorithm used by Facebook to determine what content to show in users’ News Feed.
This classification system has played a crucial role in the evolution of the user experience on the world’s most popular social platform.
EdgeRank Origin and Operation
Introduced in 2010, EdgeRank was a turning point for Facebook.
The algorithm was based on three main factors to assess the importance of each “edge” (interaction) within the platform:
- Affinity: Measured the relationship between the user and the content creator.
- Weight: Assigned different importance to various types of interactions (comments, likes, shares).
- Time decay: Privileged more recent content over less current content.
The combination of these factors determined the EdgeRank score of each piece of content, affecting its visibility in users’ News Feed.
Impact on digital marketing
The introduction of EdgeRank has had a significant impact on digital marketing strategies.
Brands and content creators have had to adapt their tactics to maximize the visibility of their posts:
- Creating engaging content to stimulate interactions
- Publishing posts at times of greatest activity of one’s audience
- Diversification of content formats (images, videos, links)
These practices have become key to achieving good placement in the News Feed and reaching a wider audience.
Evolution and overcoming
Despite its pioneering role, EdgeRank has gradually been replaced by more sophisticated algorithms. Facebook has continued to refine its content ranking system, introducing new factors and using more advanced machine learning technologies.
EdgeRank’s successor, often called the “News Feed Algorithm,” now considers hundreds of signals to determine content relevance.
These include:
- The type of content preferred by the user
- The frequency of interaction with specific friends or pages
- The context of the interaction (device used, connection speed)
- The negative feedback (hide post, report spam)
Despite the evolution, the fundamentals of EdgeRank continue to influence Facebook’s current algorithm.
Lessons learned from EdgeRank
The EdgeRank era has taught digital marketers important lessons:
- The importance of content quality over quantity
- The need to understand and adapt to the algorithms of social platforms
- The value of authentic interactions with the public
- The importance of a diversified and targeted content strategy
These lessons remain valid even in the post-EdgeRank era and apply to many other social platforms besides Facebook.
Conclusion
EdgeRank marked a turning point in the history of social media by introducing an algorithmic approach to content distribution.
Although no longer in use in its original form, its impact continues to resonate in the social media and digital marketing landscape.
Understanding the legacy of EdgeRank remains critical for anyone working in the field of social media marketing who wants to optimize their online presence.