The recent unveiling of Twitter algorithm has provided a glimpse into the mechanics that govern tweet visibility and engagement. The revelation offers users a clearer understanding of what it takes to go viral on the platform, which this blog post covers in detail. 

Twitter’s Recommendation Algorithm

Core Models and Features

The foundation of Twitter’s recommendations lies in a series of interconnected services and models that extract latent information from tweets, user behaviors, and engagement data. These models answer critical questions about the Twitter network, such as predicting future user interactions and identifying trending tweets within various communities.

The Recommendation Pipeline

Twitter's recommendation pipeline consists of three primary stages:

1. Candidate Sourcing: Fetching the best tweets from various sources.
2. Ranking: Utilizing a machine learning model to rank each tweet.
3. Heuristics and Filters: Applying additional filters, such as blocking tweets from users you've blocked or filtering out NSFW content.

This pipeline serves the "For You" timeline by connecting different candidate sources, scoring functions, heuristics, and filters.

Source: Twitter

Candidate Sources

In-Network Source

The In-Network source aims to deliver the most relevant and recent tweets from users you follow. It uses a logistic regression model to rank these tweets, with the top tweets progressing to the next stage. The Real Graph model plays a crucial role here, predicting the likelihood of engagement between users.

Out-of-Network Sources

Finding relevant tweets from users you don't follow involves two main approaches:

1. Social Graph: Analyzing engagements and follows to estimate what you might find relevant.
2. Embedding Spaces: Generating numerical representations of users’ interests and tweets’ content to identify content similarity.

Ranking Tweets

Scoring Mechanism

The ranking stage involves a neural network with approximately 48 million parameters, continuously trained on tweet interactions to optimize for positive engagement (likes, retweets, and replies). This mechanism evaluates thousands of features and outputs engagement probabilities, assigning a score to each tweet.

Heuristics and Filters

Post-ranking, various heuristics and filters refine the tweet selection to create a balanced and diverse feed. Examples include:

• Visibility Filtering: Removing tweets based on content and user preferences.
• Author Diversity: Avoiding consecutive tweets from the same author.
• Content Balance: Ensuring a mix of In-Network and Out-of-Network tweets.
• Feedback-based Fatigue: Reducing the score of tweets with negative feedback.
• Social Proof: Including only Out-of-Network tweets with a second-degree connection.

Mixing and Serving

Final Steps

In the final stage, the Twitter algorithm blends tweets with non-tweet content like ads and follow recommendations. This process ensures a diverse and engaging timeline, completing in under 1.5 seconds on average for each pipeline run.

Key Factors for Viral Success on Twitter

1. Visual Content is King

Visual elements play a crucial role in the Twitter algorithm. Tweets that include images or videos receive a significant 2x boost, emphasizing the importance of visual content in capturing and retaining audience attention.

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2. The Power of Likes and Retweets

Engagement metrics are vital to the Twitter ranking algorithm. As per this Twitter thread, likes are more influential than retweets, with each like giving a 30x boost compared to a 20x boost from retweets. Interestingly, replies are less impactful, providing only a 1x boost.

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3. The Advantage of Twitter Blue

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Subscribers of Twitter Blue, Twitter's paid service, enjoy a significant 2-4x boost in the algorithm. This indicates a clear pay-to-play advantage for those who subscribe to the service.

4. The "For You" Tab

The likelihood of your tweet appearing on someone's "For You" tab depends on various factors, including the probability of the user engaging with your tweet through likes, retweets, or spending time on it.

💡Related read: The Absolute Best Time to Post on Twitter in 2024 for More Views

5. Indirect Follow and Trusted Circle Boosts

Tweets from users followed indirectly or within the viewer's trusted circle receive additional boosts, highlighting the importance of network connections.

6. Usage of Hashtags

Hashtags will likely remain an integral part of social media because they help set parameters. Although the weight they carry in algorithms has diminished over time, their value persists. 

Incorporating AI-generated hashtags into your content creation and posting routine via vidyo.ai’s AI hashtag generator provides categorization cues, clarifying the type of material you're producing, the intended audience, and the overarching themes.

💡Related read: 15 Best Social Media Scheduling Tools in 2024

7. Grow via Threads

Twitter Threads are a great way to get your message out there, but they can be daunting to write. You can save time and effort by outsourcing the labor to vidyo.ai’s AI Content Assistant, Viddy. Type in a prompt to get hashtag-optimized Thread ideas that are easy-to-read and packed with actionable knowledge. 

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8. Engage in Conversations

Don’t just post and forget about it. The real value of your tweet lies in the audience reaction. Ensure you respond to their questions, answer their rebuttals and research their suggestions to find new tweet ideas. Building trust and credibility is at the core of developing an engaged community.

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9. Optimize Your Profile

Your Twitter profile is not a CV. It's a landing page.

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Optimize it to convert your audience to take one action:

• Subscribe
• Visit your website
• Download your guide

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Pro tip: Use birdy.so to A/B test your Twitter profile to measure conversions. 

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4 Practices That Could Diminish Your Reach

1. External Links

Including external links in tweets can be detrimental to visibility. These tweets are often marked as spam unless they achieve high engagement.

2. Lack of Text in Visuals

Tweets that feature images or videos without accompanying text are less favored by the Twitter algorithms.

3. Excessive Hashtags

Using more than a couple hashtags can trigger the algorithm's spam filters, reducing the tweet's reach.

4. Negative Interactions

Being muted, blocked, unfollowed, or reported can significantly harm a tweet's reach, as the Twitter ranking algorithm takes these negative interactions into account.

How Does the Twitter Algorithm Work?

Here's a detailed list of ranking metrics as provided by James Bachini. Note that the Twitter ranking algorithms are updated frequently:

• favCountParams (weight 30): Counts the number of times a tweet has been liked.
• retweetCountParams (weight 20): Counts the number of times a tweet has been retweeted.
• inDirectFollowBoost (weight 4): Boosts tweets from users indirectly followed by the viewer.
• inTrustedCircleBoost (weight 3): Boosts tweets from users within the viewer’s trusted circle.
• urlParams (weight 2): Counts URLs in tweets, negatively impacting the score to keep users on the app.
• luceneScoreParams (weight 2): Its function is unclear, possibly not live.
• selfTweetBoost (weight 2): Boosts tweets that reply to your own tweet, such as threads.
• tweetHasImageUrlBoost (weight 2): Boosts tweets containing at least one image URL.
• tweetHasVideoUrlBoost (weight 2): Boosts tweets containing at least one video URL.
• tweetHasTrendBoost (weight 1.1): Boosts tweets containing a trending topic.
• isReplyParams (weight 1): Indicates whether the tweet is a reply to another tweet.
• replyCountParams (weight 1): Counts the number of times a tweet has been replied to.
• multipleHashtagsOrTrendsBoost (weight 0.6): Penalizes tweets with multiple hashtags to prevent spamming.
• langEnglishUIBoost (weight 0.5): Boosts tweets written in English based on user interface language.
• reputationParams (weight 0.2): Measures the reputation of the user who tweeted.
• langEnglishTweetBoost (weight 0.2): Prioritizes tweets written in English.
• textScoreParams (weight 0.18): Measures the relevance of the tweet’s text.
• offensiveBoost (weight 0.1): Penalizes tweets marked as offensive by users.
• unknownLanguageBoost (weight 0.05): Applies to tweets written in an unknown language.
• langDefaultBoost (weight 0.02): Applies to tweets written in a language other than English.

By understanding and leveraging these insights into how the Twitter algorithm works, users can optimize their content to enhance visibility and engagement on the platform.

How to Reset Twitter Algorithm

If you're noticing that your Twitter feed isn't showing you the content you want, you might wonder how to reset the Twitter algorithm. By regularly engaging with tweets that interest you and unfollowing accounts that no longer align with your preferences, you can effectively retrain the algorithm to better suit your tastes.

Takeaway

Understanding how Twitter algorithms work is crucial for optimizing your tweets with vidyo.ai to enhance engagement. Twitter's ranking algorithm assesses factors such as likes, retweets, and replies to score and prioritize tweets. By leveraging these insights along with vidyo.ai’s AI features, you can ensure their content stands out and reaches a broader audience.

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