Thread by @aakashg0

Twitter revealed its algorithm to the world.

But what does it mean for you?

I spent the evening analyzing it.

Here’s what you need to know:

1. Likes, then retweets, then replies

Here’s the ranking parameters:

• Each like gets a 30x boost
• Each retweet a 20x
• Each reply only 1x

It’s much more impactful to earn likes and retweets than replies.

2. Images & videos help

Both images and videos lead to a nice 2x boost.

3. Links hurt, unless you have enough engagement

Generally external links get you marked as spam.

Unless you have enough engagement.

4. Mutes & unfollows hurt

All of the following hurt your engagement:

• Mutes
• Blocks
• Unfollows
• Spam reports
• Abuse reports

5. Blue extends reach

Paying the monthly fee gets you a healthy boost.

6. Misinformation is highly down-ranked

Anything that is categorized as misinformation gets the rug pulled out from under it.

Surprisingly, so are posts about Ukraine.

7. You are clustered into a group

The algorithm puts you into a grouping of similar profiles.

It uses that to extend tweet reach beyond your followers to similar people.

8. Posting outside your cluster hurts

If you do “out of network” content, it’s not going to do as well.

That’s why hammering home points about your niche works.

9. Making up words or misspelling hurts

Words that are identified as “unknown language” are given 0.01, which is a huge penalty.

Anything under 1 is bad.

This is really bad.

10. Followers, engagement & user data are the three data points

If you take away anything, remember this - the models take in 3 inputs:

• Likes, retweets, replies: engagement data
• Mutes, unfollows, spam reports: user data
• Who follows you: the follower graph

Shoutout to all the people analyzing:

@NFT_GOD
@amasad
@mxpoliakov
@0xCygaar
@xerocooleth

If you enjoyed this,

1. I write daily threads to help you grow. You may like to follow: @aakashg0

(But if you’re going to unfollow, go ahead and don’t!)

2. Consider RTing the first tweet so others can benefit:

As much as it's fun to analyze the Twitter algorithm, it's also fickle.

Most of my content doesn't make it to your feed.

Subscribe to the newsletter to get my best and deepest work: aakashgupta.substack.com

How to optimize for the algorithm:

Likes, then retweets, then replies
You are clustered - posting outside it hurts
Links hurt. Mutes & unfollows hurt
Misinformation is down-ranked
Images & videos help
Blue extends reach
Making up words or misspelling hurts

New learning: There’s also something known as “Heavy Ranker”

This heavily weights replies to replies and time spent on Tweet.

Additional learning:

Your follower to following ratio matters.

Following way more than follow you hurts.

Use lists.

The big open question is: what about bookmarks?

The predominant opinion right now is favcountparams() 30x multiplier's formula is:

Likes + Bookmarks = Favorites Count

It doesn't look to be in the code right now. Part of the problem here is what's on GitHub is incomplete.

Do you want to go the layer deeper to understand how all these code snippets and boosts work together?

I have spent the whole weekend going deeper than my Friday evening analysis.

Get the overall framework in today's newsletter: aakashgupta.substack.com/p/the-real-twi…

And here's why Twitter is the best place to get your information.

This thread was featured on the Reddit home page and Yahoo News:

Now that the algorithm is public, Elon Musk wants to update it every 24-48 hours.

Here's what he should do: