With an effort to combat fake engagement in the app, the platform is looking to crack down on automated comments submitted via third party tools in response to concern of users regarding influx of non-genuine activity.
The most concern is regarding engagement pods which refers to coordinated groups of users who work together for commenting, liking and engaging with each other’s post for boosting their reach. Data provided to SMT suggested that thousands of LinkedIn updates were being submitted every day that was being boosted by pod activity which sees genuine user updates being pushed further down the feed due to false indicators of relevance on these pod posts.
LinkedIn has stated that they were treating this matter seriously and was looking at avenues for combating pods which are organized on third party platforms.
As per the VP of Product Management of LinkedIn, they are working towards taking action against automated comments. It refers to comments which have been posted on LinkedIn through third party auto script or browser plugin without any review or human oversight. These are generally low quality comments which ends up flooding the comment section and degrades the overall experience.
Now when LinkedIn will detect automated comments, it would remove them from the Most Relevant section of the post comment which is the initial listing that users see in the app. Users can tap on this to switch to Most Recent instead but primary default display for comments is Most Relevant which means that these types of automated commends leads to generation of less reach and impact.
LinkedIn might also stop these comments from reaching beyond the network of commenter. This means that auto generated comments would only get seen by direct connection of commenter which further limits the effectiveness of this approach.
New measures for combatting third party pod activity along with improved detection which will be able to stop direct posting from automated systems to the app. This is one of the several measures which LinkedIn implemented for combatting scammers and spammers with this process using indicators like where the post is coming from for weeding out spam activities.
LinkedIn has built in measures for determining trust in automated posting from third party apps. This is an evolving challenge and LinkedIn has noted that these are difficult to counter because they have been organized outside the app but they are taking more action and further looking to implement more measures for reducing the impact of the pod posts.
LinkedIn has issued a warning that repeated use of automated commenting tools could lead to restriction of account and it signaled a shift from passive suppression to active enforcement. Now it has come up with measures for tackling third party pod activity and is focused on enhancing detection which will be able to prevent automated systems from posting on the app directly. These are just one of the several strategies the platform has been using to fight against scammers and spammers. Some of the indicators use indicators like origin of a post for filtering out any suspicious activity. LinkedIn is now moving towards an in-built mechanism for assessing the trustworthiness of automated posts from third party applications.
Combating these issues is tough as tend to originate outside the app. LinkedIn is no stepping up its e3fforts and is looking forward to introduce further measures for reducing the impact of pod posts.
It stated that they were taking this issue seriously and were looking at ways for disrupting pods which gets organized on external platforms. Initial enforcement update was carried out in November and now the company is going forward with it.
