The X Algorithm Exposed: What Really Drives Engagement (With Code Proof)

X recently made their algorithm public on GitHub, and as Haxz, we've analyzed every line of code to bring you the real story - no BS, just facts backed by actual code from the official repository.

The Truth About What Makes or Breaks Your Tweets

We spent weeks diving through X's open-sourced algorithm to understand exactly what boosts your content and what kills it. Here's what we found, with receipts straight from the code.

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1. The Engagement Predictions That Actually Matter

The algorithm predicts multiple outcomes for every tweet, then combines them into a final score. Here's exactly what it's looking for:

The Big Winners (Positive Signals)

// From PredictedScoreFeature.scala
object PredictedFavoriteScoreFeature    // Likes
object PredictedReplyScoreFeature        // Replies  
object PredictedRetweetScoreFeature      // Retweets
object PredictedVideoQualityViewScoreFeature // Video views >50%
object PredictedGoodClickConvoScoreFeature  // Quality clicks

What this means: Every tweet gets scored on the probability of getting likes, replies, retweets, and meaningful engagement. These scores are then weighted and combined.

The Silent Killers (Negative Signals)

// From PredictedScoreFeature.scala
object PredictedNegativeFeedbackV2ScoreFeature
object PredictedReportScoreFeature

If the algorithm predicts people will click "See fewer" or report your tweet, you're dead in the water.

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2. The Video Advantage Is Real

Videos longer than 10 seconds get special treatment:

// From PredictedScoreFeature.scala
object PredictedVideoQualityViewScoreFeature {
  override def isEligible: Boolean = {
    val isVideoDurationGte10Seconds = 
      (features.getOrElse(VideoDurationMsFeature, None).getOrElse(0) / 1000.0) >= 10
    hasVideoFeature && isVideoDurationGte10Seconds
  }
}

Action item: Post videos over 10 seconds to unlock the Video Quality View (VQV) scoring boost. The algorithm specifically tracks if viewers watch at least 50% of your video.

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3. The "See Fewer" Death Penalty

This is the nuclear option that destroys your reach:

// From FeedbackFatigueScorer.scala
val DurationForDiscounting = 140.days
private val ScoreMultiplierLowerBound = 0.2  // 80% penalty!

What happens when someone clicks "See fewer":

• You get an immediate 80% reach penalty to that user

• It takes 140 days to fully recover

• The penalty affects everyone who liked, retweeted, or follows you

How to avoid it: Never post divisive, annoying, or low-quality content. One "See fewer" can haunt you for months.

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4. Stop Spamming - The Algorithm Punishes Repetition

// From AuthorBasedListwiseRescoringProvider.scala
val decayFactor = 0.5  // Default
val floor = 0.25       // Minimum score

// Formula: Each additional tweet gets progressively less reach
// 1st tweet: 100% score
// 2nd tweet: 62.5% score  
// 3rd tweet: 43.75% score
// 4th tweet: 34.375% score

The math: Your 4th tweet in a row gets only 34% of the reach of your first. Space out your posts!

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5. Out-of-Network Penalty

// From RescoringFactorProvider.scala
object RescoreOutOfNetwork {
  def factor: Double = 0.75  // 25% penalty for non-followers
}

Translation: Tweets to people who don't follow you get a 25% reach penalty. Build your follower base first!

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6. Replies

// From RescoringFactorProvider.scala
object RescoreReplies {
  def factor: Double = 0.5  // 50% penalty for replies!
}

Fact: Replies get HALF the reach of original tweets. Make your replies count or post original content instead.

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7. The "GM" Tweet Problem (Why It Actually Hurts)

We found the duplicate content detection system:

// From TweetLabelRules.scala
object DuplicateContentTweetLabelDropRule
    extends DuplicateContentTweetLabelRule(Drop(TweetLabelDuplicateContent))

object DownrankSpamReplyTweetLabelRule
    extends NonAuthorWithTweetLabelRule(
      Drop(Unspecified),
      TweetSafetyLabelType.DownrankSpamReply
    )

Why "gm" tweets fail:

• Everyone replying "gm" triggers spam detection

• Repetitive content gets flagged as DuplicateContent

• Low-quality interactions hurt your engagement score

• The algorithm learns to suppress your "template" content

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8. Giveaways = Engagement Spam (Don't Do It)

The algorithm has specific detection for engagement farming:

// From UserLabel.scala
case object EngagementSpammer extends UserLabelValue
case object EngagementSpammerHighRecall extends UserLabelValue

// This drops your content for non-followers!
object EngagementSpammerNonFollowerWithUqfRule
    extends NonFollowerWithUqfUserLabelDropRule(EngagementSpammer)

What triggers engagement spam detection:

• "RT + Follow to win" patterns

• Artificial engagement spikes

• Mass follow/unfollow behavior

• Repetitive giveaway posts

The penalty: Once flagged as EngagementSpammer, you're penalized across:

• Home timeline

• Recommendations

• Search results

• Notifications

• Everything

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9. Media Tagging Doesn't Directly Boost (But...)

// From TweetMediaFeaturesExtractor.scala
val mediaTagScreenNames = getMediaTagScreenNames(mediaTags.tagMap)
featuresWithMediaEntity.copy(
  mediaTagScreenNames = Some(mediaTagScreenNames),
  numMediaTags = Some(numMediaTags.toShort)
)

The truth about tagging:

• No direct ranking boost found in code

• BUT tagged users get notified -> early engagement

• Early engagement triggers positive feedback loop

• Works best with active communities (like NFT projects)

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10. The 24-Hour Window

// From multiple sources
val MaxTweetAgeHoursParam = 24.hours
val earliestTweetId = SnowflakeId.firstIdFor(Time.now - maxTweetAgeHours)

Critical: Tweets older than 24-48 hours get dramatically reduced distribution. The first hour is EVERYTHING.

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What To Do (Backed by Code)

1. Add videos over 10 seconds - Unlocks VQV scoring

2. Space out your tweets - Avoid the author diversity penalty

3. Build genuine followers - Reduces out-of-network penalty

4. Post when audience is active - Maximize the crucial first hour

5. Create conversation starters - Replies boost your engagement score

6. Use images and media - Tracked and slightly favored

7. Stay consistent with topics - Builds stronger SimCluster embeddings

What NOT To Do (Will Kill Your Reach)

1. Never trigger "See fewer" - 140-day penalty

2. Don't spam multiple tweets - Each one gets 50% less reach

3. Avoid "gm" chains - Triggers duplicate content detection

4. No giveaways - Flags you as engagement spammer

5. Don't post mainly replies - 50% reach penalty

6. Avoid repetitive content - Duplicate detection kills reach

7. Don't rely on viral-only - Build followers or face 25% penalty

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The Bottom Line

The X algorithm is sophisticated but predictable. It rewards genuine engagement, punishes spam-like behavior, and has long memory for negative signals. Focus on quality over quantity, build real relationships, and respect the timing windows.

Most importantly: The algorithm changes, but these core principles remain. Create content people actually want to see, and the algorithm will work for you, not against you.

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This analysis is based on X's open-source algorithm available at github.com/twitter/the-algorithm. All code snippets are directly from the repository. Follow Haxz for more no-BS technical breakdowns.