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Instagram Opens Up About Recommended Posts

Educational Newsletters

Instagram’s algorithm has always been confusing. How do I get my content to show up more often? Why am I being served this suggested post? Well luckily, we might not have to guess for too much longer.

Instagram has published a new overview of how it ranks content for its ‘Suggested Posts’, or the posts that you see in your Home feed from accounts that you don’t follow in the app.

Instagram began using a lot more AI-based content recommendations in user feeds, which prompted widespread user backlash and has since seen IG double back on the decision. But even with that shift, Instagram does see AI recommendations as a key element of its future.

In other words, even if you’re not seeing as many recommendations in your home feed right now, they will be ramping up again sometime soon.

So how does Instagram select which additional content to show you in your Home feed? Here are some insights:

First off, Instagram’s engineering team outlines the focus of its recommendation system, and underlines the key aims of its approach:

  • Users spend a lot of time crafting the perfect home feed for themselves. How can we do some of that work for them and make it feel like they crafted these recommendations themselves?
  • Anecdotally speaking, users who stay engaged keep finding newer sources of interests to follow. Can we help in this act of progressive personalization a bit?


Whether people actually want an automated system to do this work for them is another question entirely, but the intended aim is to replicate human discovery with AI features, in order to enhance user engagement.

That then sees Instagram’s post recommendations fall into two categories – ‘Connected’ and ‘Unconnected’, with the latter being the posts that Instagram’s systems find and highlight, based on your interests.

The process, as you would expect, is largely based on actions you’ve directly taken in the app, such as following and liking posts. But it can also extend to the people you follow, and what they like, as a proxy for direct engagement, while some popular posts are also highlighted based on overall engagement.

But these elements are more related to its Explore surface – in the Home feed, the aim is to replicate the feel of the posts and profiles that you’ve chosen to follow, in order to make it increasingly familiar.

“Scrolling through the End of Feed Recommendations should feel like scrolling down an extension of Instagram Home Feed.”

The primary aim is to build more directly on your stated interests, as opposed to simply adding in the latest trending content.

So how does Instagram do that?

“In order to ensure that our recommendations feel similar to posts in Home Feed we prioritize accounts that are similar to accounts a user encounters in Home.

  • In the candidate selection step while training and evaluating our ranking models we ensure that the overall distribution is not skewed away from Home-based sources.
  • We follow the same freshness and time sensitivity heuristics as Home Feed to ensure that suggested posts provide a similar kind of fresh feeling as the rest of Home Feed.
  • We also ensure that the mixture of media types (like photos/videos/albums etc.) are relatively similar in Home and suggested posts.
  • For users whose immediate engagement graph is relatively sparse, we generate candidates for them by evaluating their one-hop and two-hop connections. Example: If user A hasn’t liked a lot of other accounts, we can probably evaluate the accounts followed by the accounts A has liked and consider using them as seeds. A Account Liked by A Accounts followed by the accounts A likes (Seed Accounts). The diagram below visualizes this line of thinking.


Social media platforms are in a constant state of change, which can make it difficult to fully decide on a strategy that can work for your business. But luckily, you don’t have to do that. If you need help with your organic Instagram strategy, don’t hesitate to reach out to us to schedule a free consultation.