Twitter has released its recommendation algorithm code on GitHub, providing transparency in its tweet ranking process. The code is available for everyone to see, excluding code that would compromise user safety and privacy or Twitter’s ability to protect its platform from bad actors. Twitter has also provided a more layman’s explanation of the system.

External coders found weighting data in the code base; likes and retweets are by far the most significant indicators of interest that will help to boost tweet reach.

Here’s some key points:

• The algorithm controls the Tweets displayed on the For You timeline
• The release provides high-level insight into how Twitter’s algorithms work
• Twitter is using invisible subreddits via Topics to algorithmically organize tweets
• Twitter is promoting more tweets in the ‘For You’ feed based on topical engagement
• For each user session, Twitter extracts around 1500 tweets that it believes will be of interest
• The For You timeline currently consists of 50% In-Network Tweets and 50% Out-of-Network Tweets, on average
• Twitter predicts the likelihood of engagement between two users
• Tweet ranking is conducted via a neural network optimized for positive engagement