Filings that were made by Elon Musk’s legal team in his battle with Twitter have been questioned by leading bot researchers.
A botometer which is an online tool that tracks spam and fake accounts -was used by Mr Musk in a countersuit against Twitter and while using the tool, Mr Musk’s team estimated that 33% of “visible accounts” on the social media platform were “false or spam accounts”.
However, Botometer creator and maintainer, Kaicheng Yang, said the figure “doesn’t mean anything”. Mr Yang challenged the methodology used by Mr Musk’s team and told the BBC they had not approached him before using the tool.
Mr Musk is currently in dispute with Twitter, after trying to pull out of a deal to purchase the company for $44bn (£36.6bn). A court case is due in October in Delaware, where a judge will rule on whether Mr Musk will have to buy it.
In July, Mr Musk said he no longer desired to purchase Twitter as he could not verify how many humans were on the platform.
Since then, the world’s richest person has claimed repeatedly that fake and spam accounts could be many times higher than stated by Twitter.
In his countersuit that he made public on 5 August, he claimed a third of visible Twitter accounts, estimated by his team, were fake. Utilizing that figure the team estimated that a minimum of 10% of daily active users are bots.
Twitter says it estimates that fewer than 5% of its daily active users are bot accounts.
Parag Agrawal, the new chief executive officer (CEO) of Twitter, Inc tweets, “Our estimate is based on multiple human reviews (in replicate) of thousands of accounts, that are sampled at random, consistently over time, from *accounts we count as mDAUs*. We do this every quarter, and we have been doing this for many years.”
Our estimate is based on multiple human reviews (in replicate) of thousands of accounts, that are sampled at random, consistently over time, from *accounts we count as mDAUs*. We do this every quarter, and we have been doing this for many years.
— Parag Agrawal (@paraga) May 16, 2022
Despite this problem, Twitter says it detects and deletes more than a million bot accounts every day using automated tools.
But its systems do not catch them all, and Twitter accepts that millions of accounts slip through the net. However, it says they make up a relatively small proportion of its 217 million daily active users.
Some bot experts claim Twitter has a vested interest in undercounting fake accounts.
“Twitter has slightly conflicting priorities,” says Mr Davis.
“On the one hand, they care about credibility. They want people to think that the engagements are real on Twitter. But they also care about having high user numbers.”
The vast majority of Twitter’s revenue comes from advertising, and the more daily active users it has, the more it can charge advertisers.
Mr Kearney believes Twitter could have built stronger tools for finding fake accounts.
“Twitter is perhaps not leveraging all the technology they possibly could to have the clearest answer,” he says.
Mr Yang believes Twitter’s methodology is fairly strong and says if he had its data, he “would probably do something similar to Twitter” to verify accounts.
But he also agreed that the characteristics of a bot need to be better defined.
“It’s important to have people from both sides sit down together and go through the accounts one by one”, he says – to agree on an accepted bot definition.
However, both sides appear done talking. In October, in a court in Delaware, we’ll get a clearer idea of who the judge thinks is right he says.