In the aftermath of the Cambridge Analytica scandal I remember hearing - likely in an interview in a BBC Radio4 programme on the topic (unfortunately I don't recall more than that) - a claim that scammers were using past sharing behaviour on social media to identify the people who were most gullible and then targeting them (using social media's targeted advertising tools) for scams and confidence tricks.

However, googling this issue doesn't find much to corroborate this specific claim. I can only find more general statements which seem to imply it's feasible and even probable... but little hard evidence of it actually happening.

Some relevant things would seem to be:

  • A quite prescient 2016 Forbes piece "Should We Fight Fake News By Banning Gullible People From The Internet?" which notes sharers of fake news could easily be assigned a "gullible" flag that "advertisers would likely find of great interest".
  • Accounts (example) of sharing of fake news being used to target users for advertising (to recruit followers) by fake news sites.
  • A Bloomberg piece on "shady advertisers" mentions "Facebook’s targeting algorithm is so powerful... they don’t need to identify suckers themselves—Facebook does it automatically" but unfortunately it's not clear how exactly those "suckers" are targeted and exploited.
  • Update: A short but punchy IEEE piece (thanks to Elliot Svensson's answer for that) includes a statement that "my concern now is the people who are making themselves targets. People paint a bull’s-eye on their back when they share, respond to, or like certain social media posts. My advice is to check your facts before you show scammers you’re susceptible to fraud.". However, it seems to be short of hard evidence for its claim that "Sometimes what follows fake facts is identity theft and stolen financial information" and the best it can offer is that sharing a fake news story "could have been a machine-learning classifier to help predict the gullibility of potential marks" (my emphasis).

None of this is quite specific enough though. Ideally I'm looking for some more concrete specific examples as evidence: sharing of what sort of nonsense was subsequently used to target what sort of users and scam them how?


1 Answer 1


The actions of scammers may never come to light, so it may be impossible to find hard evidence that scammers are using Facebook's and Twitter's powerful tools in this way. But it would not make sense for scammers not to use these powerful tools.

According to this article:

...a sucker list... has the names and contact information of people who either have fallen for scams before or are likely to now because they have responded in some way to fake articles or email. The list might include those who liked or shared a Facebook post that was making the rounds in support of underappreciated Vietnam veterans—which turned out to be a joke.The photo in the post was of actors in the movie Tropic Thunder, including Ben Stiller and Jack Black. Yet many people believed the men in the photo to be real veterans. This particular post seems to be harmless. It was not asking for money. But, it could have been a machine-learning classifier to help predict the gullibility of potential marks.

The information of people fooled like that can be collected and added to a sucker list. Scamming operations and organized crime rings develop these lists to increase their profits. The lists are guarded and refined.

Although such lists are not openly for sale, they are out there. A BBC article describes one such database with 160,000 names of repeat scam victims, some of whom receive 60 pieces of mail each day.


Advertisers know that Facebook will provide them a list, for advertising purposes, of people who share their posts. They will also provide a list of people similar to those who share their posts. It's a feature called "Custom Audiences / Engagement". See this link for Facebook's sales pitch to this effect... it is not hard to imagine how an Engagement Custom Audience can be used for this purpose. From Facebook:

About Engagement Custom Audiences

An Engagement Custom Audience is a Custom Audience made up of people who have engaged with your content across the Facebook family of apps and services.

"Engagement" refers to actions like spending time viewing your videos or opening your lead form or Canvas. Using Engagement Custom Audiences, you can target ads to people who've taken these actions. You can also use it as a source for a Lookalike Audience, which will let you find people who are similar to those who've engaged with your Facebook content.

Facebook Advertising Help

Twitter also provides this kind of tool to advertisers: Follower targeting.

Target people based on who they follow

Follower targeting helps you connect with the people who are likely to be interested in your business.

It works by displaying your Twitter Ads campaigns to people who are similar to the followers of the usernames you select.


Consider focusing on one of these followers targeting categories:

Competitors: Target the usernames of businesses who offer similar products and services.

Complimentary brands: Include the usernames of businesses who aren’t direct competitors, but who target a similar audience. For example, a fitness app might want to target the followers of athletic clothing brands, running shoe companies, and gyms.

Industry media: Try targeting the usernames of news sites, blogs, TV shows, magazines, etc. that focus on your industry or target demographic.

Influencers: Focus on the usernames of individuals who are influential in your industry. For example, a retail company could target the followers of popular fashion bloggers.

Similar audiences: You can also target users who are similar to the people who already follow you.

twitter for business

It might not be too hard for a researcher to prove that retweeting or liking fake news is an invitation to scammers: she would simply set up two new accounts, one of which will retweet the fake news, and see if it gets more scams. I, too, would be interested if such a study had been done!

  • 3
    This source doesn't give evidence that the sharing behavior was used. It just says "it could have been a machine-learning classifier to help predict the gullibility of potential marks", and that the information "can be collected and added to a sucker list". The BBC article doesn't describe information about sharing fake news in the sucker list it reports on, just the other type of information (people who are repeat victims of scams).
    – De Novo
    Commented Oct 4, 2018 at 20:27
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    Pay attention to the claim here. You're basically re-iterating the question with more statements about how this would be "feasible and even probable... but little hard evidence of it actually happening."
    – De Novo
    Commented Oct 4, 2018 at 20:51
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    @DeNovo, since we don't expect Facebook to publish the advertising-user history of scammers for our perusal, I don't think we can expect to see evidence that this is happening. Nevertheless, it would be implausible to claim "scam advertisers on Facebook are not using powerful tools provided by Facebook to identify the best targets for their scams." I think the Question may be answered in this way, in acknowledgement of the absence of evidence. Commented Oct 4, 2018 at 21:00
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    @elliotsvensson: No, conjecture in absence of evidence isn't accepted here.
    – Oddthinking
    Commented Oct 5, 2018 at 1:41
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    @DeNovo, but we don't know that the list had been compiled according to retweets / shares of fake news. Commented Oct 6, 2018 at 22:40

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