2 min read
X has taken a major step toward transparency by publishing the full codebase for its “For You” timeline. The move is Elon Musk’s way of giving the public an unprecedented glimpse into how posts are curated and ranked on the platform.
The repository contains nearly 65,000 lines of code across hundreds of Scala files, shedding light on the mechanics behind X’s recommendation system. The “For You” feed now clearly reflects X’s priorities of promoting high engagement and diverse content from both accounts users follow and those they do not. Posts from Blue subscribers and those containing rich media such as images or videos are also given visibility boosts.
What the Released Code Reveals About Ranking Factors
The newly released algorithm highlights how X assigns weight to user actions that determine post visibility in the “For You” feed.
The most powerful signal is when a user replies to a post and the original author engages with that reply, which strongly boosts visibility. Other factors include the likelihood of receiving direct replies, interaction with the author’s profile, and engagement with conversations by opening and spending time reading threads.
Actions such as retweets and likes still influence ranking but have a much lower impact. Video completion rates are counted as well, though their contribution is minimal compared to text-based engagement.
Level of Transparency Matters
This full release marks a first-of-its-kind moment for a major social network, allowing creators, analysts, and researchers to study exactly what drives post distribution.
By opening the algorithm to the public, X has taken a step toward building user trust and leveling the playing field for creators seeking visibility.
However, this openness also raises concerns about possible system manipulation, as bad actors could exploit the ranking signals to artificially boost their reach.
What This Means for Users and Creators
For creators and brands, this means designing content that sparks meaningful conversation and encourages direct replies. Everyday users can expect a more personalized “For You” experience, with recommended posts not only from people they follow but also from a wider pool of creators.
For policymakers and researchers, the release of the code provides a valuable reference for future discussions about algorithmic transparency and regulation. It also sets a new standard for openness in social media operations.
