Signals the System Cares About

How the PhoenixScorer quantifies the value of your tweets.

Multi-Target Engagement Prediction

X's recommendation system doesn't rely on a single metric. PhoenixScorer predicts the Log Probabilities of a user performing various actions.

Action Type Description Internal Name
Favorite Liking a tweet ServerTweetFav
Reply Replying to a tweet ServerTweetReply
Retweet Reposting content ServerTweetRetweet
Click Expanding tweet details ClientTweetClick
Dwell Time Time spent viewing the tweet DwellTime
Share Sharing via DM or Copy Link ClientTweetShare

Negative Actions

These behaviors trigger immediate downranking and can place an author on a recommendation blacklist:

  • Not Interested: User flags content as irrelevant.
  • Block Author: User blocks the creator.
  • Mute Author: User mutes the creator.
  • Report: User reports the tweet for violations.

Weight Combination Logic

The final score is a sum of these probabilities multiplied by their respective weights. The platform frequently adjusts these weights to optimize user experience.

Fun Fact: In many iterations, a Repost (Retweet) is weighted several times higher than a Like (Favorite) because it signifies strong endorsement. Replies that spark further conversations are weighted even more heavily.