Ranking Tweets with TensorFlow

As a global, public communications platform, Twitter strives to keep users informed with relevant, healthy content. Originally, Twitter presented Tweets in reverse-chronological order. As the community became more connected, the amount of content in users' home timelines increased significantly. Users would follow hundreds of people on Twitter -- maybe thousands -- and when opening Twitter, they would miss some of their most important Tweets. To address this issue, we launched a "Ranked Timeline" which shows the most relevant Tweets at the top of the timeline -- ensuring users never miss their best Tweets. A year later we shared how machine learning powers the ranked timeline at scale.