x-algo-engagement

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:

1. Input: User history + candidate posts
2. Output: Log probabilities for each action type per candidate
3. 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