"In a post on GitHub on Tuesday, X provided an accessible write-up about its feed-generating code, along with a diagram of how the program works. What has been revealed isn't particularly earth-shattering-but it does provide a peek behind the algorithmic curtain. The diagram shows that, when sifting about for content to feed a particular user, the site's algorithm considers their engagement history (what posts they've clicked on, etc.) and surveys recent in-network posts."
"It also conducts a machine-learning-based analysis of "out-of-network" posts - as in, content from accounts that the user doesn't necessarily follow - that it believes the user might also find appealing. The algorithm then filters out certain kinds of posts, including ones that come from blocked accounts or that are associated with muted keywords, as well as content that has been deemed too violent or spam-like."
In 2023 Twitter partially open sourced its algorithm after Elon Musk's acquisition, with claims of increased transparency. Critics called that code release "transparency theater," saying it was "incomplete" and failed to explain organizational decisions or why the code behaved as it did. X reopened its algorithm repository after a Musk promise to publish the algorithm and provide updates every four weeks. A GitHub write-up and diagram outline a feed generator that uses engagement history, recent in-network posts, and machine-learning analysis of out-of-network posts. The system filters blocked accounts, muted keywords, violent or spam-like content, then ranks posts by predicted user appeal. The disclosure offers a limited but clearer peek into feed mechanics.
Read at TechCrunch
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