Social Media Spam Bots and Fake Engagement

Social Media Article
20 mins

What exactly are social media spam bots, who is behind them, and why are they used to create fake engagements on social content? Let’s get to the bottom of this strange online phenomenon.

When social media posts are full of fake engagement, it’s very hard for us to tell what we’re getting right and what we’re getting wrong in our social media strategy – because most of the likes and comments on this and many of our other posts can be traced back to social media spambots. On the surface, this might seem like a good thing for us – who could complain about all those easy-earned likes and comments?

We would actually much rather have a modest number of great genuine engagements with our content than such a large number of fake ones. Fake engagements skew our social data, which makes it far harder for us to work out which posts are genuinely getting the best reaction from our legitimate followers.

Why is this happening?

Social spam bots exist to earn people followers, sales leads, and ultimately, money. These bots are really just algorithms used in conjunction with social media profiles to create engagements with other people’s content. This, in turn, attracts engagement with the profile linked to the algorithm, from both real users and other bots.

Bots will often specifically target content or users with some connection to whatever it is they are ultimately trying to sell. So Target Internet’s page is a magnet for B2B/digital marketing bots, whilst singletons might find themselves targeted by bots posing as remarkably amorous social users with supermodel looks. In one recent study, 30% of social media users were found to have been fooled into thinking bots were real people.


Why is this happening on social media?

Where other public parts of the web have enjoyed recent wins in their battles with spam content, social media remains a playground for spammers. Think of Google’s success in cracking down on spammy links; think of recent improvements to spam comment detection on blogging platforms; and then compare that with the situation on Twitter, where an estimated 7% of profiles were spam-bots as of 2015.

The beauty of Twitter and Facebook is that they give people a platform to say just about whatever they want. Unfortunately, and in spite of legal and practical counter-measures such as spam detection through machine-learning, this liberal policy gives spammers a better chance to operate successfully than they might find on more tightly regulated parts of the web.

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