LinkedIn has recently shared a new technical overview of its efforts to combat viral spam, which also provides some interesting notes on how its Feed algorithm works, and how content gains traction in the app. It could help in your strategic planning – or at the least, it’ll help you understand the factors that weigh into LinkedIn’s algorithmic flow, which ultimately dictates post reach.
Not The Good Spam
First up on the chopping block is LinkedIn notes that its platform is not designed to maximize the reach of popular posts the way that other social apps are:
“LinkedIn is not designed for virality but on occasion, posts that result in significant engagement in the form of likes, reactions, comments, and reshares in a short period of time could be considered viral.”
LinkedIn is more aligned with community building and niche relevance, which is why amplifying all the most popular posts doesn’t really work within the context of the app. Posts that generate a ton of engagement will still be more widely shared. Of course, anyone who’s trying to maximize their in-app performance now works toward post optimization, in whatever way possible.
So, how do you do it then? How can you maximize post reach? In its overview, LinkedIn explains how its system detects potentially viral content and stops potentially violative posts. Here’s what LinkedIn basically tells us are the key factors that weigh into the performance of posts:
The post author.
Engagement signals.
Temporal signals (velocity of likes/reactions, shares, comments, and views).
In terms of post author, LinkedIn says that its system measures:
“The influence and popularity of [members posting and engaging with a post] as their action might expose the post to a lot more members creating a cascade effect which makes the post go viral. Here, we use features such as followers and connection counts, diversity in industry, location, and level of the network (connections and followers) of these members.”
Note that LinkedIn used the term ‘members’ here, not ‘users’. The reason is that LinkedIn doesn’t share data on actual user counts, only total members. When it comes to engagement signals, LinkedIn says that it then measures the likes and reactions for each post, along with shares, comments, and views.
So, velocity is important, at least in this case. The main factors in gaining maximum traction on LinkedIn are:
The number of followers that you have.
The number of connections that you have.
Diversity considerations (vaguer).
Your location.
The seniority of users in your network.
The velocity of engagement with post.
LinkedIn doesn’t specifically note that either likes, comments, or shares weigh more heavily, but that’s also likely another element in its ranking system.
The Wrap
It’s best to start building your LinkedIn audience and hoping that most of them stick around as followers. Followers count more than just basic connections, however, both followers and connections are factors. You can check out your follower count in your LinkedIn Feed settings. After this, all you need to do is to start posting engaging content, which isn’t necessarily easy, but is doable, with some tediousness.
When it comes to spam detection, LinkedIn says that its systemic updates have led to significant improvements in its detection and removal of violative content, with the overall percentage of views on spam declining by 7.3%.
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