Elon Musk revealed Twitter’s algorithm source code last week.

Musk's decision comes amid concerns over the social media's impact on everyone, including the spread of misinformation and the manipulation of public opinion.

By making the source code public, Musk hopes to address such concerns by increasing transparency and allowing for greater community input into the platform's development.

Twitter mentioned in its blog post that they uploaded the source code in two repositories on GitHub, the code sharing platform.

But what many of us want to know is how to use it in our favor, to create the right type of content that will help us grow our Twitter account and build our Personal Branding over time.

We dived into the source code along many Twitter Brains that have done the legwork on how to make it work in your favor.

Are likes, retweets and replies a ranking factor? Let’s find out!

Twitter Algo Cheat Sheet Code

User Indexsy did a good Cheat Sheet with most of the information found about the reveal, see embed below — and for more details, keep reading!

Adding images is good for algorithm

Twitter user Akash Gupta (@aakashg0) figured from the source code that the algorithm decided 30x boost for each like, 20x for each retweet and only 1x for a reply. This clearly means earning likes is more impactful than retweets and replies. He further added that videos and images give a boost of 2x.

Twitter Blue Impact

Paying the monthly fee for blue check marks can extend the organic reach.

Repercussions of engagement

Engagement can be hurt by various actions, such as mutes, blocks, unfollows, spam reports, and abuse reports. Listed below are some of the algorithm outputs:

Misspellings are ‘Unknown Language’

Words with misspellings are considered as an unknown language with a rating of 0.01. Double-checking your spelling is crucial for reaching a wider audience on Twitter, especially if you're not subscribed to Twitter Blue and can't edit your tweets.

Review your tweets, don’t make mistakes.

Twitter’s Primary Data Points

Twitter has three primary data points: engagement data such as likes, retweets, and replies, user data such as mutes, unfollows, and spam reports, and the follower graph indicating who follows you.

There is more to Likes, Retweets and Replies…

In a different series of tweets, another Twitter user @steventey found that this algorithm is more complex than just likes, retweets, and replies.

On Twitter, your "reputation score" can be reduced by several negative feedback loops, including getting blocked, muted, abuse or spam reports, and unfollows (although to a lesser extent).

Users are categorized into clusters

Twitter's algorithm categorizes users into clusters based on the type of content they regularly post. News organizations, Bollywood celebrities, and football accounts, for instance, are each placed in their own cluster. This feature allows Twitter to personalize users' feeds based on their interests.

However, if a user posts content that falls outside their designated cluster, also known as "out of network" content, it can negatively impact their reach.

Sticking to a specific niche can, therefore, increase the chances of having their content boosted and seen by their intended audience.

What’s missing from the source code?

Steven has reported that Bookmarks, which is Twitter's newest addition to tweet metrics, appears to be absent from the publicly accessible code, in case you are curious about it.

TweetHunter co-founder Tibo says Elon’s decision to open Twitter algorithm was a brilliant move for reasons like transparency, addressing the problems and scope to fair game to attract more creators.

It remains to be seen how Twitter will respond to Musk's move and whether it will choose to embrace the open-source model.

Nonetheless, the move by one of the world's most influential tech figures is likely to spark further discussion and debate around the role of social media.

So far, Twitter has released only a part of the source code; there is more to come.