What was EdgeRank?
EdgeRank was Facebook’s first algorithm for sorting your News Feed. It came about in 2010 when Facebook needed a way to handle the growing amount of content on the platform. The algorithm decided what posts you’d see based on three main factors:
- Your connection to the poster
- The type of content
- How recent the post was
EdgeRank only stuck around for about a year. By 2011, Facebook replaced it with more complex machine learning algorithms. But EdgeRank laid the groundwork for how Facebook shows you content today. It was the first step in personalizing your feed and managing information overload.
How did EdgeRank work?
EdgeRank was Facebook’s early algorithm for ranking content in your News Feed. It used three main factors:
- Affinity: This measured how close you were to the person or page posting content. The more you interacted with them, the higher the affinity score.
- Weight: Different types of posts had different values. Comments were worth more than likes, and photos often ranked higher than plain text.
- Time decay: Newer posts got priority over older ones. Fresh content was more likely to show up in your feed.
These factors worked together to decide what you’d see when scrolling through Facebook. For example, a recent photo from your best friend would rank higher than an old text post from a page you rarely engage with.
Why did Facebook replace EdgeRank?
Facebook replaced EdgeRank because it couldn’t keep up with the platform’s growth. As you scrolled through your News Feed, EdgeRank struggled to handle the massive amount of content and data.
In 2011, Facebook switched to a machine learning approach. This new system could process over 100,000 factors, compared to EdgeRank’s three main components.
The updated algorithm gave you a more personalized experience. It could better predict what content you’d like to see and engage with. This change helped Facebook show you more relevant posts and ads.
While EdgeRank is gone, its core ideas still shape how Facebook ranks content today. The platform continues to prioritize posts based on your interests, interactions, and timeliness.
What’s the relevance of EdgeRank for marketers today?
EdgeRank may be outdated, but its core ideas still matter for Facebook marketing. To boost your page’s visibility, focus on creating engaging content that sparks real conversations. Avoid clickbait and like-baiting tactics that can hurt your reach.
Instead, aim for posts that naturally encourage comments, shares, and reactions. This increases your organic reach without running afoul of Facebook’s current algorithm.
Remember, quality trumps quantity. A few well-crafted posts can do more for your brand than a flood of mediocre content. Try mixing up your content types – videos, images, and text posts – to keep your audience interested.
Building a loyal fan base is key. Respond to comments and messages promptly to foster a sense of community around your page. This ongoing engagement helps ensure your future posts reach more of your followers’ feeds.
How did EdgeRank evolve into Facebook’s current algorithm?
EdgeRank, Facebook’s original News Feed algorithm, used just three factors to rank content. But things have changed a lot since then.
Today’s Facebook algorithm is way more complex. It uses machine learning and over 100,000 factors to decide what you see in your feed.
The new system looks at things like:
- Who posted the content?
- How you’ve interacted with similar posts
- When it was posted
- What type of content it is
This evolution helps Facebook show you more relevant content. But engagement is still key – the more you interact with a post, the more likely you’ll see similar content in the future.