The Pinterest Algorithm

As we discussed in class this week, algorithms are becoming an increasingly significant part of our daily lives. One app that consistently makes me question how its algorithms work is Pinterest. While many apps gradually introduce content that you might be interested in, Pinterest seems to latch onto your preferences a little too quickly. You click on a single image of a nicely decorated room, and suddenly your entire feed is filled with posts like “12 Best Interior Design Choices.” Some recommendations even seem completely irrelevant; like the motorsport images on my feed, for example. I have absolutely no interest in cars and motorcycles, and have never watched a race in my life. So, what drives these recommendations? To better understand how Pinterest decides what to show me, I downloaded my personal data from the app and researched how its algorithms work.

Inferences made about your interests

An important thing to remember, is that algorithms are just sets of instructions for computers. People’s interests are complex, and therefore algorithms are sometimes unable to reflect them accurately. You can easily see this when you look at your own Pinterest data. It will include a list named ‘Inferences made about your interests’, which shows you about seventy topics that Pinterest assumes you’re interested in. My list includes things that I agree with, like Comic Illustration, Web and App Design, and Drawing.  But it also includes Kart Racing, Auto Racing Events and Rallying, and a few celebrities that I have never heard of.

Algorithms aren’t always right

The Pinterest algorithm is driven by four key factors: domain quality, pin quality (an image in the app is called a ‘pin’), pinner quality, and topic relevance. Domain quality measures how frequently the website linked to a pin is visited, while pin and pinner quality are based on how much interaction users and their content generate. The most intriguing factor, however, is topic relevance—how does Pinterest determine your interests in the first place?

Though I haven’t found a concrete answer, one Reddit comment offered an interesting perspective. It suggested that Pinterest’s algorithm may have worsened in recent years due to stricter data tracking laws in the EU.

The specifics of what data Pinterest tracks are unclear. The app allows you to turn off ‘Inferred signals about you,’ but the definition of those ‘signals’ is quite vague. My guess is that this specific tracking algorithm used to be what made the app’s recommendations so relevant, but due to the recent limitations of privacy laws, they are more restricted to the use of in-app data. As a result, recommended pins are now mostly based on pins that you’ve clicked on only once, maybe even by accident.

Feed personalisation for all apps

Fortunately, Pinterest allows you to refine your feed with relative ease. In addition to unchecking the ‘Inferred signals’ box, the app also lets you customize which interests, pins, boards, followed accounts, viewed pins, and saved pins should shape your personalized feed. Though it’s not perfect—I’ve unchecked the ‘Motorsport’ interest multiple times only to see it reappear—it has successfully filtered out other unwanted content from my feed.

This level of control is something other apps could benefit from. For instance, TikTok only lets you flag a post as “Irrelevant for me,” but even after doing so, I still see a lot of similar content. Pinterest’s ability to fine-tune user preferences, despite some flaws, offers a more tailored experience. If more platforms adopted this model of user customization, it would significantly improve how well feeds reflect what users actually want to see, leading to a better overall experience in the age of algorithmic curation.