Social Media: Fake followers on Instagram

Every now and then we hear about influencers that are apparently so keen on success, fame and money that they buy in likes and fans.

It is understandable, because the Instagram algorithm determines what content you get to see based on the number of likes and comments (engagement). Smart tricks to generate more reach may sound attractive as many influencers earn money based on their reach.

That money can be earned with it is also the reason that many new Instagrammers buy followers and likes. Because from 10,000 followers you can already earn good money with sponsored content. Reason why we – Honest London – always do a thorough check on fake followers and fake engagement.

How do we recognise fake influencers?

But how do we recognise an influencer with fake followers?

  • We check the engagement rate: does an influencer have one hundred thousand followers and only dozens of likes? Then the followers are probably purchased.

  • We check the followers ourselves: do we see many followers with weird names, or without profile photos? Then the followers are probably purchased.

  • We check the growth of the account: did the number of followers increase or decrease in a short amount of time? Probably followers were purchased.

  • We also have software that will check the validity of the account providing engagement rate/CTR and more.

In addition, we always check the comments. Do we only see comments with an emoji or just two or three words? Then the comments are probably purchased, or a result of comment pods.

Comment pods are groups of influencers who respond to each other briefly every day to beat the Instagram algorithm. The pods come in all shapes and sizes. And although the accounts that participate are real, it is still not authentic, and it does not do anything qualitative for your brand or.

Fortunately, we are increasingly aware of the characteristics of fakers on the web. And Instagram and other social media platforms will hopefully look at ways to prevent fakers to fool the algorithm.

Lauren BeechingComment