// Reference for X algorithm engagement types and signals. Use when analyzing engagement metrics, action predictions, or understanding what signals the algorithm tracks.
Explain why posts get filtered from the X feed. Use when analyzing why a post was removed, not shown, or filtered out of recommendations.
Explain the Phoenix ML model architecture for X recommendations. Use when users ask about embeddings, transformers, how predictions work, or ML model details.
Explain the complete X recommendation algorithm pipeline. Use when users ask how posts are ranked, how the algorithm works, or want an overview of the recommendation system.
Calculate and explain X algorithm engagement scores. Use when analyzing post ranking, understanding score weights, engagement potential, or why one post ranks higher than another.
| name | x-algo-engagement |
| description | Reference for X algorithm engagement types and signals. Use when analyzing engagement metrics, action predictions, or understanding what signals the algorithm tracks. |
The X recommendation algorithm tracks 18 engagement action types plus 1 continuous metric. These are predicted by the Phoenix ML model and used to calculate weighted scores.
Defined in home-mixer/candidate_pipeline/candidate.rs:
pub struct PhoenixScores {
// Positive engagement signals
pub favorite_score: Option<f64>,
pub reply_score: Option<f64>,
pub retweet_score: Option<f64>,
pub quote_score: Option<f64>,
pub share_score: Option<f64>,
pub share_via_dm_score: Option<f64>,
pub share_via_copy_link_score: Option<f64>,
pub follow_author_score: Option<f64>,
// Engagement metrics
pub photo_expand_score: Option<f64>,
pub click_score: Option<f64>,
pub profile_click_score: Option<f64>,
pub vqv_score: Option<f64>, // Video Quality View
pub dwell_score: Option<f64>,
pub quoted_click_score: Option<f64>,
// Negative signals
pub not_interested_score: Option<f64>,
pub block_author_score: Option<f64>,
pub mute_author_score: Option<f64>,
pub report_score: Option<f64>,
// Continuous actions
pub dwell_time: Option<f64>,
}
| Action | Proto Name | Description |
|---|---|---|
| Favorite | ServerTweetFav | User likes the post |
| Reply | ServerTweetReply | User replies to the post |
| Retweet | ServerTweetRetweet | User reposts without comment |
| Quote | ServerTweetQuote | User reposts with their own comment |
| Follow Author | ClientTweetFollowAuthor | User follows the post's author |
| Action | Proto Name | Description |
|---|---|---|
| Share | ClientTweetShare | Generic share action |
| Share via DM | ClientTweetClickSendViaDirectMessage | User shares via direct message |
| Share via Copy Link | ClientTweetShareViaCopyLink | User copies link to share externally |
| Action | Proto Name | Description |
|---|---|---|
| Photo Expand | ClientTweetPhotoExpand | User expands photo to view |
| Click | ClientTweetClick | User clicks on the post |
| Profile Click | ClientTweetClickProfile | User clicks author's profile |
| VQV | ClientTweetVideoQualityView | Video Quality View - user watches video for meaningful duration |
| Dwell | ClientTweetRecapDwelled | User dwells (pauses) on the post |
| Quoted Click | ClientQuotedTweetClick | User clicks on a quoted post |
| Action | Proto Name | Description |
|---|---|---|
| Not Interested | ClientTweetNotInterestedIn | User marks as not interested |
| Block Author | ClientTweetBlockAuthor | User blocks the author |
| Mute Author | ClientTweetMuteAuthor | User mutes the author |
| Report | ClientTweetReport | User reports the post |
| Action | Proto Name | Description |
|---|---|---|
| Dwell Time | DwellTime | Continuous value: seconds spent viewing post |
The PhoenixScorer (home-mixer/scorers/phoenix_scorer.rs) calls the Phoenix prediction service:
probability = exp(log_prob)fn extract_phoenix_scores(&self, p: &ActionPredictions) -> PhoenixScores {
PhoenixScores {
favorite_score: p.get(ActionName::ServerTweetFav),
reply_score: p.get(ActionName::ServerTweetReply),
retweet_score: p.get(ActionName::ServerTweetRetweet),
// ... maps each action to its probability
}
}
favorite_score of 0.15 means 15% predicted chance of likereport_score reduces overall rankingMIN_VIDEO_DURATION_MS/x-algo-scoring - How these signals are combined into a weighted score/x-algo-ml - How Phoenix model predicts these probabilities