Tesla CEO Elon Musk shook Twitter shares on Friday when he said he would stop acquiring the $ 44 billion social network while investigating the share of fake and spam accounts on the platform.
Although Musk later clarified that he remained committed to the deal, he continued to push the issue of fake accounts. He wrote on Twitter that his team will make its own analysis and expressed doubts about the accuracy of the figures that Twitter announced in its latest financial documents.
In its first-quarter earnings report this year, Twitter acknowledged that it had a number of “fake or spam accounts” on its platform, along with legitimate monetized daily active users or users (mDAUs). The company said: “We have conducted an internal review of a sample of accounts and estimate that the average of counterfeit or spam accounts in the first quarter of 2022 is less than 5% of our mDAU in the quarter.
Twitter also admitted that it has overestimated the number of users by 1.4 million to 1.9 million users in the last 3 years. The company wrote: “In March 2019, we launched a feature that allowed people to link several separate accounts together to conveniently switch between accounts,” revealed Twitter. “An error was made at that time, so the actions taken through the primary account resulted in all linked accounts being reported as mDAU.”
Although Musk may be justifiably curious, experts in social media, disinformation and statistical analysis say his proposed approach to further analysis is grossly inadequate.
Here’s what the CEO of SpaceX and Tesla said he would do to determine how much spam, fake and duplicate accounts exist on Twitter:
“To find out, my team will make a random sample of 100 followers of @twitter. I invite others to repeat the same process and see what they find.” He clarified his methodology in the following tweets, adding: “Choose any account with many followers” and “Ignore 1000 followers first, then choose every 10th. I’m open to better ideas. “
Musk also said, without providing evidence, that he chose 100 as the sample size number for his survey because that’s the number Twitter uses to calculate the numbers in their earnings reports.
“Any reasonable random sampling process is good. If many people independently receive similar results for% of fake / spam / duplicate accounts, this will be indicative. I chose 100 as the sample number because that’s what Twitter uses to calculate <5% fake / spam / duplicate. "
Twitter declined to comment when asked if its description of its methodology was accurate.
Facebook co-founder Dustin Moskowitz weighed the issue through his own Twitter account, saying Musk’s approach was not accidental, using too small a sample and leaving room for massive mistakes.
He wrote: “I also feel that ‘I don’t trust the Twitter team to help get the sample out’ is a kind of red flag.”
BotSentinel founder and CEO Christopher Buzi said in an interview with CNBC that his company’s analysis shows that 10% to 15% of Twitter accounts are likely to be “authentic”, including counterfeits, spammers, fraudsters, malicious bots, duplicates and ‘Single target hate accounts’, which are usually targeted and harassing people, along with others who deliberately spread misinformation.
BotSentinel, which is largely supported by crowdfunding, independently analyzes and identifies non-authentic Twitter activity using a combination of machine learning software and teams of people who check. The company tracks more than 2.5 million Twitter accounts today, mostly English-speaking users.
“I don’t think Twitter realistically classifies ‘fake and spam’ accounts,” Buzi said.
He also warns that the number of non-authentic accounts may appear higher or lower in different corners of Twitter, depending on the topics discussed. For example, more inauthentic accounts tweet about politics, cryptocurrency, climate change and covid than those discussing controversial topics such as kittens and origami, BotSentinel found.
“I just can’t understand that Musk is doing anything but trolling us with this stupid sampling scheme.”
Carl T. Bergström
Author, “Calling Bulls —“
Carl T. Bergstrom, a professor at the University of Washington who co-authored a book to help people understand the data and avoid being lured by false claims online, told CNBC that sampling from a hundred followers each a Twitter account should not serve as a “proper check” for a $ 44 billion acquisition.
He said that the sample size of 100 is an order of magnitude smaller than the norm for social media researchers studying such things. The biggest problem Musk would face with this approach is known as choice bias.
Bergstrom wrote in a statement to CNBC: “There is no reason to believe that the followers of the official Twitter account are a representative sample of accounts in the platform. Bots may be less likely to follow this account to avoid detection. They may be more likely to follow to look legitimate. Who knows? But I just can’t understand that Musk is doing anything but trolling us with this stupid sampling scheme. “
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