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Understanding the concept of Metaverse
Recommendation algorithm
The recommendation pipeline has four steps:
- Candidate sourcing - Fetch the best tweets from different recommendation sources
- Ranking - Rank tweets such that the most relevant ones appear first in the feed.
- Filtering - Apply heuristics and filters to create a balanced and diverse feed.
- Mixing non-tweet content like Ads, Follow Recommendations, and Onboarding prompts.
The recommendation pipeline runs 5 billion times per day and completes in under 1.5 seconds on average.
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Candidate sourcing
Gets the best 1,500 recent tweets:
- 50% from people you follow (In-Network)
- 50% from people you don't follow (Out-of-Network)
In-Network
- Uses a logistic regression model to rank the recent tweets of people you follow. The higher the likelihood of engagement between you and another user, the more of their tweets will be included.
Out-of-network
- Uses a social graph of engagements to find tweets that people you follow have recently engaged with, and tweets liked by people who are similar to you.
- Uses an embedding space of users and tweets to determine what tweets and users are similar to your interests.
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Ranking
Ranking is achieved with a 48M parameter neural network that is continuously trained on tweet interactions to optimize for positive engagement (e.g. Likes, Retweets, and Replies). This ranking mechanism takes into account thousands of features and outputs ten labels to give each tweet a score, where each label represents the probability of an engagement.
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Apply heuristics and filters
- Visibility Filtering: Remove tweets from accounts you block or mute.Â
- Author Diversity: Avoid too many consecutive tweets from a single author.
- Content Balance: Deliver a fair balance of In-Network and Out-of-Network tweets.
- Feedback-based Fatigue: Lower the score of tweets that you provided negative feedback around.
- Social Proof: Exclude Out-of-Network tweets without a second degree connection to the tweet i.e. ensure someone you follow engaged with the tweet or follows the tweetâs author.
- Coďťżnversations: Provide more context to a Reply by threading it together with the original tweet.
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