What's an Algorithm, Really?

People throw the word "algorithm" around when talking about user engagement with their social media content posts but I don't think they really know what that means from software engineering perspective.

The word "algorithm" is often used casually when referring to the way social media platforms control what content users see in their feeds, but the actual underlying technology can be much more complex than a simple algorithm.

In essence, these platforms use a combination of algorithms and machine learning models to personalize each user's feed based on their past behavior, engagement, and preferences. The goal is to show users content that they are most likely to be interested in and engage with, while also balancing the interests of the platform itself (e.g., promoting content that keeps users on the platform for longer or generates more revenue).

Here is a high-level overview of how some of these platforms might determine what to show in a user's feed:

YouTube: YouTube uses a combination of algorithms to determine what videos to recommend to users. One algorithm considers a user's watching history, likes, and dislikes, while another algorithm considers the popularity of videos (e.g., how many views, comments, and likes a video has received). The platform also takes into account the relevance of a video to the user's search history, location, and other demographic information.

LinkedIn: LinkedIn uses a similar approach to YouTube, considering a user's past behavior (e.g., posts they have liked or shared), their network, and the popularity of content (e.g., how many views, likes, and comments it has received). The platform also uses natural language processing and machine learning models to understand the content of posts and recommend them to users based on their interests.

Instagram: Instagram uses a combination of algorithms to determine what content to show in a user's feed. One algorithm considers a user's past behavior (e.g., the accounts they follow and the posts they like or comment on), while another algorithm looks at the popularity of content (e.g., how many likes and comments a post has received). The platform also takes into account the timeliness of posts, as well as the relevance of a post's hashtags and location information.

Facebook: Facebook uses a similar approach to Instagram, considering a user's past behavior, the popularity of content, and the relevance of posts to the user. The platform also takes into account the type of content (e.g., whether it's a text post, photo, or video), as well as the user's network (e.g., posts from friends versus posts from pages they follow).

It's important to note that these algorithms and machine learning models are constantly evolving and being updated, so this is just a snapshot of how they might work at a given moment in time. Additionally, the specifics of how each platform determines what to show in a user's feed can be quite complex and proprietary, so this is just a general overview.