Facebook has become the advertising outlet of choice for many of the world’s businesses and companies. Whenever there is a new product to test, a service to announce or event to promote, many organisations turn to Facebook to post news of the development.
To enable this, Facebook allows users to create pages devoted to specific topics. Visitors can then “like” the page and then receive updates about the topic as well as connect with others with similar interest. The number of likes is therefore an important measure of the popularity of the page and there is considerable prestige in having many likes.
That is handy for Facebook which allows businesses to promote their pages using adverts targeted at certain groups of users who may be interested in the content. It is possible, for example, to target people with specific interests or those who live in the US and so on. These ads are a major source of income for Facebook.
However there is another way to promote Facebook pages. In recent years, a secret industry has emerged that sells likes to anyone willing to pay. These paid services inflate the interest in a Facebook page using “like farms” that generate likes on demand. Little is known about these services or how they generate likes. In particular, nobody is quite sure whether the likes come from automated bots or from paid human workers.
Today, Emiliano De Cristofaro from University College London and a few pals around the world provide the first systematic investigation into the nature of like farms and how they operate.
Their approach is relatively straightforward. These guys begin by setting up 13 Facebook pages about “Virtual Electricity” but without any content. In every page description, they included the sentence “This is not a real page, so please do not like it.”
They then used Facebook ads to generate visits to five of these pages, targeting users in the US, France, India, Egypt and worldwide, respectively. Their budget was six dollars a day up to a total of $90 the 15 days.
At the same time, they also used four “like farms” to generate visits to the remaining eight pages. These like farms were BoostLikes.com, SocialFormula.com, AuthenticLikes.com and MammothSocials.com. With each of these like farms, they targeted worldwide or US users. These services charged between $70 and $190 for 1000 likes in 15 days.
The team then measured the activity on each page over the following 22 days using Facebook’s own statistics and by crawling the public information from the liker’s profiles and by studying the list of liked pages as well as friend lists.
The results are revealing. First, De Cristofaro and co analysed the ability of the genuine Facebook ad campaigns to attract likers from different parts of the world. The US campaign generated 32 likes, divided more or less equally between men and women, the vast majority of whom were actually based in the US.
The Indian and Egyptian campaigns generated over 500 likes each, almost all from people in India and Egypt respectively. The French campaign generated 44 likes, mainly from people in France. Curiously, the worldwide campaign generated about 500 likes, almost all of them from India.
De Cristofaro and co also analysed the Facebook likers themselves. These people had more than 300 friends each on average, which is similar to the global average. However, these Facebook users liked between 600 and 1000 other pages compared to regular Facebook users who average about 40. “In other words, our honeypot pages attracted users that tend to like significantly more pages than regular Facebook users,” they conclude.
The likers from the like farms are even more strange. While the number of likes gathered from Facebook campaigns increase slowly over time, the numbers from most like farms jump suddenly in steps.
“With AuthenticLikes, we observed likes from more than 700 profiles within the first four hours of the second day of data collection,” say De Cristofaro and co. After that, there was not a single additional like.
The team say this is likely to be the result of automated bots operating a set of fake profiles. Just why Facebook is unable to prevent this kind of activity is not clear.
However, the team says there is evidence that some like farms operated a more sophisticated type of liking that aimed to mimic real Facebook users much more closely. This would be much harder to clamp down on.
The owners of these profiles are unlike ordinary Facebook users as well. For example, they tend to like huge numbers of other pages, between 1200 and 1800.
That’s strange, say the team. “Since our honeypot pages both for Facebook and like farm campaigns explicitly indicated they were not “real”, we argue that a vast majority of the garnered likes are fake,” they conclude.
That’s an interesting study, albeit a small one. It exposes the activity behind like farms for the first time, concluding that many of the likes bought in this way are fake. That can hardly be much of a surprise to most people.
What is also worrying, though, is that the users attracted through genuine Facebook ad campaigns also seem to be different from average Facebook users. And that raises the question of where they come from.
De Cristofaro and co are quick to add a proviso to their work. “We stress that our findings do not necessarily imply that advertising on Facebook is ineffective, since our campaigns were specifically designed to avert real users,” they say. “However, our work provides strong evidence that likers attracted on our honeypot pages, even when using legitimate Facebook campaigns, are significantly different from typical Facebook users.”
That something that advertisers may want to research in more detail themselves. In the meantime, De Cristofaro and co are planning more research to study like farms in more detail. We will be watching.
Ref: arxiv.org/abs/1409.2097 : Paying for Likes? Understanding Facebook Like Fraud Using Honeypots
What’s next for AI regulation in 2024?
The coming year is going to see the first sweeping AI laws enter into force, with global efforts to hold tech companies accountable.
Three technology trends shaping 2024’s elections
The biggest story of this year will be elections in the US and all around the globe
Four lessons from 2023 that tell us where AI regulation is going
What we should expect in the coming 12 months in AI policy
The FTC’s unprecedented move against data brokers, explained
It could signal more aggressive action from policy makers to curb the corrosive effects that data brokers have on personal privacy.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.