Twitter Takes Its Recommendation

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Algorithm ‘Open-Source’. What’s Covered In The Code? Vanessa Dias Vanessa Dias Content Specialist Apr 5, 23 | 4 min read ✓ Human crafted content twitter algorithm open source Need content for your business? Find top writers on WriterAccess! Try for free If you’re a digital marketer who’s always wished you could take an inside peek into Twitter’s recommendation algorithm, you’re in luck. Two different Twitter source code repositories just landed on GitHub, and marketers have wasted no time combing through them in search of answers.

But how much were eagle-eyed marketing pros able to learn from the repositories, and what do the findings mean for those in the digital marketing sector moving forward? Let’s take a closer look at what you need to know, What’s Covered in the Code? Along with America Mobile Number List the GitHub drop, Twitter also released a blog post further explaining a few things, including some of the details revealed within the source code. Although many people would like to know about Twitter’s algorithm and how it functions, the release focuses primarily on the “For You” feed and how the recommended tweets you see are chosen.



According to Twitter, the recommendation process consists of three different stages: Candidate Sourcing: In which large batches of high-value tweets are selected via various recommendation channels Ranking: A machine learning process that sorts tweets according to additional perceived value Filtering:The portion of the process where non-relevant tweets are removed from the feed (e.g., tweets you’ve seen previously or content that may be NSFW) CEO Elon Musk first informed users of his intentions to release this information a while ago – March 2022, before he purchased Twitter.