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.
X Algorithm Engagement Signals
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.
PhoenixScores Struct
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 Types by Category
Positive Engagement (High Value)
| 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 |
Sharing Actions
| 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 |
Engagement Metrics
| 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 |
Negative Signals
| 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 |
Continuous Actions
| Action |
Proto Name |
Description |
| Dwell Time |
DwellTime |
Continuous value: seconds spent viewing post |
How Scores Are Obtained
The PhoenixScorer (home-mixer/scorers/phoenix_scorer.rs) calls the Phoenix prediction service:
- Input: User history + candidate posts
- Output: Log probabilities for each action type per candidate
- Conversion:
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
}
}
Signal Interpretation
- Scores are probabilities (0.0 to 1.0): P(user takes action | user sees post)
- Higher = more likely: A
favorite_score of 0.15 means 15% predicted chance of like
- Negative signals have negative weights: High
report_score reduces overall ranking
- VQV requires minimum video duration: Only applies to videos >
MIN_VIDEO_DURATION_MS
Related Skills
/x-algo-scoring - How these signals are combined into a weighted score/x-algo-ml - How Phoenix model predicts these probabilities
By