First Draft Club

The Algo’s Just Not That Into You

Something weird is happening on Farcaster, and it’s time we talk about it openly. This isn’t just “home feed doing home feed things.” It’s much deeper and more concerning. 

Some casts are skyrocketing with 10k+ views from accounts that have 1k followers. Meanwhile, longtime casters with 100k+ followers are seeing reach crater by 50%. The math doesn’t add up…unless something’s being boosted.

We’re watching artificial amplification play out in real time and this experiment needs to end now before more trust is lost. 

The algorithm cares more about engagement quality than raw follower numbers. There are several Dune queries who show the most popular casters by the numbers, but they do NOT align with the Farcaster Leaderboard. We know that not everyone’s engagement is weighted equally, and most of us have come to begrudgingly accept this fact. 

The home and trending feed have always favored certain accounts, and as little as two engagements with those accounts can amplify a cast to trending.  We see it and have come to terms with it. 

But recently, we’ve seen a new trend emerge: artificial algorithmic boosting…to levels never before seen on Farcaster…and we need to stop dancing around the subject and talk about it. 

A user with 1,000 followers might have a highly active niche audience, while someone with 250,000 might have a large but disengaged base…but we have Dune queries to show us how “active” each account’s followers have been over the last 7 and 30 days. 

Very large accounts (6-figure followings) tend to have about 50% of their followers be considered “active” under this metric (active=have casted, liked, or recasted).

Newer accounts skew higher because many are only a few weeks old, so most of their followers are obviously active. 

If the algorithm is boosting based on more active followers, it could explain the great discrepancies we are seeing in reach, so we need to look deeper. 

A new tool has emerged that lets us look into the number of unique accounts that interacted with a user's content in the last 30 days, and the data is very telling. This data counts everyone on the protocol, not just those with good spam labels. 

If you think your engagement has gone down a lot over the past few weeks, you aren’t imagining it. Usually, if 2-3% of your followers interact with your casts, you are doing great.  But what if most of the people who follow you never even see your casts in the latest version of the algorithm? Spoiler alert: they don’t. 

Let’s compare some of the biggest, most established accounts on the network to newer accounts who I believe are being artificially amplified. 

These accounts all have well over 100,000 followers each (even more on the protocol!), cast daily, and consistently engage back with the network. Their content and casting patterns have not changed noticeably over the last 30 days. 

The number of unique accounts they have reached in the last 30 days and how much their engagement is down is as follows:

15,400 (down 67%)
7,500 (down 49%)
1,500 (down 29%)
2,700 (down 36%)
6,500 (down 55%)
4,200 (down 54%)

Now let’s compare this to one of the new accounts that I believe are being purposely placed into many users’ home feeds (note that these accounts have 1,000-3,000 followers). 

10,500

The number of views on many of their casts are also between 10,000 and 18,000 views. Remember, the data above shows interactions, but even more people have seen these casts!

A user with 1,000 followers getting seen by 10,000+ people requires external amplification.

That reach doesn’t emerge organically. The algorithm chose to show them beyond their organic social graph. 

Observing a few examples of weird reach/follower ratios doesn’t necessarily prove systemic bias.  Visibility is complex and can swing based on timing, interaction graphs, and reposts by top casters, but the math doesn’t add up without boosting.

The people getting boosted didn’t necessarily ask to be. Now they’re targets of backlash; they are victims as well. 

Meanwhile, those who have not had this type of algorithmic boost feel invisible and demoralized, even if they’ve consistently added value to the community.

It’s creating a toxic imbalance that erodes trust across the board. We can politely say “vibes are off” and tell people to just mute what they don’t want to see, but that’s not going to solve the issue at hand. This is deeper than engagement FOMO.
We are watching something we’ve invested time into start to resemble the very platforms we came here to escape.

The algorithm may be silent, but its choices are loud. If it is hand picking winners, the rest of us should stop pretending we’re playing the same game. Invest your time here accordingly.

"...we need to stop dancing around the subject and talk about it. [...]

"If you think your engagement has gone down a lot over the past few weeks, you aren’t imagining it. Usually, if 2-3% of your followers interact with your casts, you are doing great. But what if most of the people who follow you never even see your casts in the latest version of the algorithm? Spoiler alert: they don’t."

"Meanwhile, those who have not had this type of algorithmic boost feel invisible and demoralized, even if they’ve consistently added value to the community."

Mad respect to @pichi for speaking out about these worrisome patterns, backing them up with data, and connecting the dots so the rest of us can get a better view. 

She's clearly speaking out of love and care. Hope the Merkle team takes these concerns seriously.

Pi-chi.eth Artist /animeoutcasts
Hosting: /sakura /kyoto /anime-manga /farcasterunion

https://portrait.so/pichi

Word-Slinger-in-Chief /slowcore-hq | Senior Editor | GenX eldergoth | dark ambient music nerd | contemplative animist /blxstonesnctuary 🏳‍🌈

Thanks so much for reading and sharing!!!

I super appreciate it!

300 $TIPN

I think posting them as casts first is a good idea, especially when you're covering a topic of broad general interest to Farcaster. Paragraph posts (even in the mini-app) just don't reach as many readers as casts do.

Thanks so much. I’ve got to get better about making these into Paragraph articles next! But I like testing them here first and seeing if they are worth expanding on.

Much love to you for writing this. It's a service to the network, and to all of us who aren't able to follow and investigate these things as closely as you do.

Also, your "first draft" is beautifully written. It's much more polished than some of the "finished drafts" that have crossed my desk as a copy editor... lol.