Collateral Damage by Automated Engagement System

Background

Over the last 12 months, there has been a rise of automated engagement systems (AES), which is used to increase LI exposure. This is understandable, given that participating in engagement pods consume a lot of time. In particular, it consumes even more time when participating in the pods that are facilitated on Whatsapp or Telegram chat groups.

The automated engagement systems also pose another attractive value proposition – guaranteed engagements by either likes or comments. This is often what other manual engagement pods are lacking.

How it works

Users will sign up for the membership and also install the Google Chrome extension. Whenever a user makes a post, the user will submit the post link to the chrome extension. The chrome extension will then activated to get other members in the same pod to to:

  1. automatically like the submitted post
  2. automatically comment on the submitted post

When posting, the automated pod system always has a set of comments pre-created by the pod leaders or system admins. These are very generic comments. The user has the flexibility to manually update the comments, which would be made on their post.

Likewise, as a user who is a member of the pod, its profile will also be used to do exactly the same things when other members submit their posts. However, it’s also worth noting that users can change the settings whether their profile will participate in the like / comments automatically.

Problems

It’s quite possible that the use of the automated engagement system will cause more damage to one’s LI profile than the benefits it could provide. Below are some of the observed and known problems.

  1. Engagement rate – most members within the pod will have at least the liking functionality turned on but it’s estimated that less than 50% of the members on any pod will have the commenting functionality turned off. What this means is, the posts are less likely to achieve a high virality score due to the number of comments provided by the pod.
  1. Misuse and abuse of the commenting functionality – As the way how the system is designed, users will have the ability to have complete control over how others are commenting on their posts. This itself is a double sided sword. There has been multiple evidence and personal experiences that other users are abusing this functionality where inappropriate comments are being made. This is very dangerous because it could damage the personal brand of the user. This is also the very reason why most users have this functionality turned off to reduce the profile damage.
  1. Quality of the comments – Similar to the above, the total control of the comments is a welcome feature when used properly. However, most users tend to use the default comments created by the system. This means the quality of the comments will often be low as they tend to consist of: Thanks for sharing, great post, Really like your post etc. Over the time, this type of comments will become obvious and turn off your targeted buyers, who closely follow your works, profile and posts.
  1. Members of the pod – pod generally consists of the members from all over the world. Whilst it may seem like the user is well connected all over the world, in reality it makes little sense unless you are high profile. The more troubling issue is when the members are from different cultural backgrounds. Imagine a user auto like an Italian post, though this issue is mitigated by separate pods based on countries.
  1. Size of the pod – The number of the members could really vary from pod to pod. Some could have less than 10 whilst some could have more than 50. Though, from the personal experience with multiple pods within the automated pod system, the common size appears to be around 20 – 30. I have personally never seen anything larger than 50. Such small pod size makes the gaming activities obvious to both human and machine.
  1. Randomisation – There is no control built into the system to disguise the gaming activities. This again leaves the gaming activities obvious to both human and machine.
  1. Timing of the engagement – because the members are from all over the world with different time zones, the automated system makes the engagement timing rather weird and strange. For example, an Australian user posts in the morning, and other US based pod members automatically engage with the post, even though it’s actually midnight in their timezone. This is illogical and would leave trail for LI algorithm to detect the gaming activities
  1. Technology – Similar like other LinkedIn automated systems such as Linked Helper, the automated engagement pod system utilises the Chrome extension as the technology backend. It’s well documented this type of technology often leaves a digital footprint within the Chrome session and LinkedIn has been actively warning the uses of Chrome extension for automation. This subsequently allows LinkedIn to be able to detect the gaming activities thus increasing the odds of having the account being terminated by LinkedIn. 

Summary

In summary and at the first glance, AES may be useful and solve the problems to help users get more exposure. However, as one digs deeper and as described above, AES in reality would have done more damage than good to a user’s profile. 

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