LinkedIn has provided an update on its efforts to combat fake engagement in the app, with the platform looking to crack down on automated comments submitted via third-party tools, in response to user concerns about an influx of non-genuine activity.
In July last year, we reported on LinkedIn’s evolving focus on artificial engagement in the app, based on user reports of a steady rise in fake engagement activity.
The most notorious concern in this respect is engagement pods, which are coordinated groups of users who work together to comment, like and engage with each other’s posts, in order to boost their respective reach. Data supplied to SMT suggested that thousands of LinkedIn updates were being submitted each day that were being boosted by pod activity, which then sees genuine user updates pushed further down the feed, due to false indicators of relevance on these pod posts.
LinkedIn informed us at the time that it was taking this seriously, and that it was exploring various avenues to combat pods, which are generally organized on third party platforms. And in November, LinkedIn provided an update on its efforts in combating pods and fake engagement.
And now, LinkedIn’s VP of Product Management Gyanda Sachdeva has shared a new update on its evolving spam focus.
As per Sachdeva: “We’re gonna’ take some action against automated comments. These are comments that are posted to LinkedIn through a third party auto-script or a browser plugin without any human oversight or review. Usually, when they are posted like this and are low quality, they end up flooding the comment section and degrade the overall experience.”
Sachdeva says that, now, when LinkedIn detects automated comments, it will remove them from the “Most Relevant” section of the post comments, which is the initial listing that users see in the app.
Users can tap on this to switch to “Most Recent” instead, but the primary default display for comments is “Most Relevant,” which will mean that these types of automated comments end up generating a lot less reach and impact.
Sachdeva says that LinkedIn may also stop these comments from reaching beyond the commenter’s network. That would mean that auto-generated comments are only being seen by the commenters’ direct connections, further limiting the effectiveness of this approach.
Finally, Sachdeva says that if a member continuously posts automated comments, they may also have their account restricted.
So, new measures to combat third-party pod activity, with improved detection that will be able to stop direct posting from automated systems to the app. This is one of several measures that LinkedIn’s implementing to combat spammers and scammers, with this process using indicators like where the post is coming from to weed out disingenuous activity.
Though how that relates to scheduling tools is another question, but presumably, LinkedIn has built in measures to determine trust in automated posting from third party apps.
It’s an evolving challenge, and LinkedIn has previously noted that these are difficult to combat because they are organized outside the app. But it is taking more action, and looking to implement more measures to reduce the impact of pod posts.
