Ah, this one. It was discussed on HN back in May [0].
The main problem is that they aren't performing an analysis of mDAUs, as you imply. Their datasets are:
1. Followerwonk Random Sample – "Marc wrote code to randomly select public accounts from Followerwonk’s active database, and passed them to SparkToro for analysis. Casey on our team further scrubbed this list and ran 44,058 public, active accounts through our Fake Followers spam analysis process"
2. Aggregated Average of the Fake Followers Tool - "Over the last 3.5 years of operation, SparkToro’s Fake Followers tool has been run on 501,532 unique accounts, and analyzed thousands of followers for each of those, totaling more than 1 billion profiles (though these are not necessarily unique, and we don’t keep track of which profiles were analyzed as part of that process). ... We’ve included it for comparison, and to show that an analysis that includes simply random Twitter accounts (vs. those that have been recently active) may not be as accurate."
3. All Followers of @ElonMusk on Twitter
4. Active Followers of @ElonMusk on Twitter
5. Random Sample of 100 Users Following the @Twitter account
The last three datasets are obviously not relevant for getting a good estimate of mDAU authenticity. The second dataset may include inactive/duplicate accounts, and it's not clear how random the account selection is. The first dataset (as well as the second, to some extent) suffers from only including public, active accounts, which very much is not the same population Twitter is working with:
> We define mDAU as people, organizations, or other accounts who logged in or were otherwise authenticated and accessed Twitter on any given day through twitter.com, Twitter applications that are able to show ads, or paid Twitter products, including subscriptions.
In particular, note that Twitter has no requirement that mDAUs have public activity.
In addition, the article contains this bit at the bottom, which further reinforces that these numbers aren't comparable:
> We are not disputing Twitter’s claim. There’s no way to know what criteria Twitter uses to identify a “monetizable daily active user” (mDAU) nor how they classify “fake/spam” accounts. We believe our methodology (detailed above) to be the best system available to public researchers. But, internally, Twitter likely has unknowable processes that we cannot replicate with only their public data.
Their methodology is very detailed. Maybe Twitter can post theirs to give more confidence in their 5%.
They used multiple datasets and posted the calculated mDAU for each.