10 Things we knew from open-sourced Twitter algorithm

Twitter revealed its algorithm to the world as open source on GitHub.

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

I hope this helps you. You know someone will benefit from this, share it with him/her, a friend or colleage.