Selling The Dream
What an inauthentic Twitter account with hundreds of thousands of fake Followers and Twitter’s CFO have in common
According to Nick Bilton (author of “Hatching Twitter”): “Twitter knew about all its fake Followers, and always has — eliminating just enough bots to make it seem like they care, but not enough that it would affect the perceived number of active users on the platform.” (February 2018)
Upon closer inspection of what takes place under Twitter’s hood, it becomes apparent that Nick’s assertion perfectly describes Twitter’s approach to dealing with inauthentic accounts.
“M LeMont” (aka @MisterSalesman) is a Twitter account that, as of September 16th, 2020, reflects having nearly 375 thousand Followers (and with more than 1.5 million tweets):
It is worth immediately highlighting that “M LeMont” is Following nearly 375 thousand accounts (and that the account is Following more accounts than it has as Followers).
In January 2018, in a report titled “The Follower Factory,” The New York Times made use of a clever tactic to identify fake Twitter Followers. Their approach involves plotting an account’s Followers (earliest to most recent) against the date each respective account was created. The example below, courtesy of New York Times graphics editor, Rich Harris, does a great job illustrating patterns that signal inauthentic Followers:
Here is the New York Times style scatterplot for the Followers of @MisterSalesman:
The top Amazon review from the United States cuts right to the chase, alleging that the book’s author “has multiple personalities and profiles to switch in and out of to market his/her book” and pointing out the lack of engagement on tweets from the @MisterSalesman account:
“M LeMont” offers up vanilla insights to the account’s hundreds of thousands of Followers — including hits such as the “first order of business when I log on to Twitter is to follow back” (and then links out to their site):
Following back, indeed, emerges as the core tactic utilized by @MisterSalesman in building their Twitter audience of nearly 375 thousand Followers.
Following & Followers Overlap
Hence, it would be fair to categorize “M LeMont” as a follow-for-follow account.
More specifically, follow-for-follow accounts are generally Following a similar number of accounts (often a very large number, e.g. 367,453) as they have as Followers. Moreover, follow-for-follow accounts tend to be followed back by a large percentage of the accounts they are Following.
Most large follow-for-follow accounts have leveraged automation to create the illusion of support for their account/content (i.e. people are more likely to accept a tweet from an account with 100K Followers vs. a tweet from an account with 10 Followers as being a commonly held viewpoint, for example).
This tactic, which admittedly Twitter has more recently made adjustments to their policies to limit, was incredibly widespread for many years (and where it would be impossible for Twitter to be unaware of the downstream repercussions). Effectively it involves running a script (to simplify, this may be viewed as a piece of code) that automates the following process. For example, someone can compile (or acquire) a list of accounts that appear to be running a script which is set to automatically follow back any account that follows it. Next, they would simply set their script to follow said list of accounts, allowing them to very quickly have at their disposal an account that, on the surface at least, appears to have lots of support behind it (i.e. a large Followers count). In reality, the vast majority (but certainly not all) of accounts that run scripts which follow back any account that follows theirs are fake accounts. There is zero incentive for Twitter to remove these fake accounts, as many of them tweet, in turn creating advertising inventory, and thus revenue, for Jack Dorsey’s company.
The fact that 93% of the accounts being followed by @MisterSalesman happen to be accounts that are following “M LeMont” back is something that simply does not occur organically.
It is worth noting that Twitter Rules prohibit “aggressive following”:
When Twitter suspends the account of @MisterSalesman (which is inevitable), it is paramount that they also suspend the fake accounts inflating the Followers count of “M LeMont.” Else, chances are another “M LeMont” type of account will be created by the same operators, who will in turn backfill the account’s Followers with many of the same fake accounts, once again succeeding in creating the illusion of support.
Twitter tends to only remove a handful of core accounts while claiming to proactively mitigate information operations/platform manipulation, rather than removing the full ancillary networks that are being utilized by nefarious actors.
Hyperactive, Automated, and Anti-Trump
The @MisterSalesman account has, on average, tweeted 398 times per day since being created more than a decade ago (September 2010).
Over the past 6 days the account has averaged more than 500 tweets per day and where 90% of its tweets were posted via third-party posting automation tool, The Social Jukebox:
Below is a sampling of recent @MisterSalesman tweets pushing anti-Trump sentiment and with the United States presidential election less than 10 days away:
Included among tweets/content being amplified by “M LeMont” is a retweet of “Indict Agent Orange” (@RicoMuscatel):
Pinned Tweet: Follow-For-Follow Matryoshka Dolls
Each of the 8 accounts — in addition to “M LeMont” (@MisterSalesman) who wrote the book on gaining (100,000) Twitter Followers — are accounts Social Forensics would use the “inauthentic account” label to describe. Based on the accounts’ behavior (not their content), inauthentic account is an apt descriptor because each account has leveraged fake accounts and automation to inflate their Followers counts.
Describing these accounts as inauthentic does not mean the accounts are not being controlled by real people; it simply references the coordinated, inauthentic process by which the accounts have acquired their large (and deceptive) Followers counts.
One of the accounts mentioned in the Pinned Tweet of @MisterSalesman is “Uniquely Me #Resist #FBR #FBRParty” (aka @PsychicHealerC), an anti-Trump, inauthentic “Resistance” account that is Following more than 140 thousand accounts:
Selling The Dream
While @MisterSalesman—an inauthentic Twitter account with hundreds of thousands of fake Followers — is selling one dream, Twitter’s Chief Financial Officer, Ned Segal, is selling another equally dishonest dream to Wall Street.
Whether “M LeMont” is the account of a well-intentioned pseudonymous author vs. there being more nefarious forces at work is irrelevant. Either way, @MisterSalesman is using Twitter to shill their book on gaining Twitter Followers when the account’s own Followers consist of hundreds of thousands of fake accounts.
Segal, a former Goldman banker, functionally has full control over what Twitter’s monetizable daily active users (mDAU) growth trajectory — a key metric investors look to when valuing Twitter’s stock — looks like:
Twitter has grown their mDAU base by 70 million since Segal took the helm as Twitter’s CFO in August 2017. Included among Twitter’s mDAU — which as of last quarter was reported at 186 million — are hundreds of thousands of fake accounts that inflate the Followers count of @MisterSalesman (and many other accounts).
Outside of the “M LeMont” account, Twitter continues to wildly inflate their mDAU stats by purposefully including millions of accounts that are of zero value to advertisers, yet that create advertising inventory which Twitter happily monetizes.
Effectively what this means is that Segal (and by extension, Twitter)—by opaquely and selectively enforcing their platform manipulation rules—are well-equipped to sell Wall Street a narrative grounded in the application of an arbitrary “scrub” vs. one that more transparently reflects a healthy, growing business.
Social Forensics maps and monitors social connections and activity.
We create purposefully designed tools to manage social data analytics needs across various industries. Our focus is audience segmentation and identifying coordinated inauthentic behavior (CIB) across social media platforms.
Geoff Golberg is an NYC-based researcher (and entrepreneur) who is fascinated by graph visualization/network analysis — more specifically, when applied to social networks and blockchain activity. His experience spans structured finance, ad tech, and digital marketing/customer acquisition, both at startups and public companies.
Geoff is the Founder/CEO/Janitor of Social Forensics.