The Shift From Who to What: Understanding Social Media Interest Graphs

How was your last scroll on your social media app of choice? Did you have a quick, efficient trip through your feed or (like most of us) did you get sucked in for a fifteen- or twenty-minute jaunt that ended in a three-minute video on vintage cake recipes? As social user habits have changed, that kind of time commitment is only possible with the interest graph algorithm model—and it’s something you should be taking into account with your social strategy. 

Social media’s start had a very defined purpose: keeping up with friends and family. If you’re a millennial or older, you likely remember this clearly—and you remember how resistant social media users were to algorithmic changes that moved more toward trending topics and user-indicated interests. However, short-form video’s meteoric rise to social strategy as well as search-based social trends (among other factors) has knocked old-school social algorithms off the radar. Interest graphs represent a pivotal shift away from traditional social graphs, offering new engagement opportunities for digital marketers. Let’s look at the latest algorithmic changes and what metrics to pay attention to when posting.

What is a Social Graph?

For years, social media success was measured by follower count, which directly impacted your overall reach and engagement levels. While this is still an important metric to nurture, it’s no longer the end-all-be-all gold standard. With a social graph, though, it determined how well your social posts would perform. Facebook pioneered this concept, connecting friends and family and fostering new connections between shared relationships. Social graphs gave local businesses a leg up with relevancy to the local community, but made finding a new audience more difficult.

However, the rise of influencers changed this dynamic, building new ways of connecting online focused on following unknown accounts that created content relevant to the individual user.

What is an Interest Graph?

The interest graph model connects social users with posts relevant to their interests. Social algorithms gather information based on metrics such as likes, watch time and shares to serve more similar content to the user. With this, you don’t need to follow someone in order to see their posts, though following someone does influence how often you’ll see their content.

Features like Instagram’s Explore page and TikTok’s For You page are perfect examples of the interest graph, though you’re seeing its concept more and more on virtually all social sites. Following-only feeds now tend to be opt-in features rather than the expected default option.

For digital marketers, there’s a real opportunity to grow by simply using modern best practices to manage your social presence and find your niche audience.

Further Factors: Connected vs. Unconnected Reach

The difference between social and interest graphs comes down to one main theme: connection.

How people discover content is vastly different from one model to another. Content discovery in social interest graphs is more fluid than simply seeing what followed accounts post. Algorithms take your user interests into consideration, serving up content that your followed accounts engaged with, that your actions on the app indicate you may be interested in or that is simply trending across the site at the moment.

It’s much more complex than the social graph method of content discovery, which relied almost exclusively on followers interacting with (and preferably resharing) your posts.

The relationship between follower and followed account also varies wildly with interest graphs.

What Is the Difference Between Social Graphs and Interest Graphs?

Within interest graphs, two types of reach affect how your content makes it to social users. Instagram has been open with their definition for this differentiation, which they call connected and unconnected reach. Let’s define each term:

Connected reach: Content shown to your existing followers

Unconnected reach: Content shown to audiences beyond direct connections (non-followers)

So why do these two algorithmic factors matter? Let’s use Instagram as an example to explore.

While we may not have details on how most social apps’ algorithms work, we can use what Instagram has shared about their algorithmic logic to make informed decisions on your posting strategy and what metrics to prioritize. We broke down insights into their algorithm in more detail here.