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Effective URL: https://www.socialmediatoday.com/news/LinkedIn-Shares-Algorithm-Insights/648254/
Submission: On April 24 via api from CH — Scanned from DE

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An article from


LINKEDIN SHARES INSIGHTS INTO HOW ITS FEED ALGORITHM WORKS IN OVERVIEW OF SPAM
TACKLING EFFORTS

Published April 20, 2023
By
Andrew Hutchinson Content and Social Media Manager
 * 
 * 
 * 
 * 
 * 

LinkedIn has shared a new technical overview of its efforts to combat viral spam
in the app, which also provides some interesting notes on how its feed algorithm
works, and how content gains traction in the app.

Which 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.

First off, 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. But posts that generate a heap of engagement will still be more
widely shared as a result – and of course, everyone trying to maximize their
performance in the app is working towards post optimization, however they can.

So how can you maximize post reach?

In the overview, LinkedIn explains how its system detects potentially viral
content, and stops potentially violative posts:

“As soon as a piece of content surfaces, the existing ML classifiers act based
on the immediate features that can be computed, such as author and content
related features. If it is found to be spam or policy-violating, then we either
take an automatic action or send it for human review to decide on the action to
be taken. For the content that is still present on the platform, we monitor the
engagement signals, temporal signals, and spam related signals to detect the
potential for viral spam during the content lifecycle on the platform.”



So LinkedIn’s telling us that the key factors that weigh into the performance of
a post are:

 * 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 uses the term ‘members’ not ‘users’, because LinkedIn doesn’t
share data on actual user counts, only total members.

In terms of engagement signals, LinkedIn says that it then measures the likes
and reactions for each post, along with shares, comments, and views.



Keep up with the story. Subscribe to the Social Media Today free daily
newsletter

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“We derive various features from these such as temporal sequences of counts and
velocity of likes, reactions, shares, comments, and views. These act as the
strongest signal for the cascading effect happening in the network.”

So velocity is important, but the main factors in gaining maximum traction on
LinkedIn are likely as you would expect:

 * The number of followers that you have
 * The number of connections that you have
 * Diversity considerations (more vague)
 * 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.

So, best to start building your LinkedIn audience, and hoping that most of them
stick around as followers. Follower counts logically count for more than basic
connections, though both are factors - but it is also worth noting that once
someone has connected to you, they can still unfollow you and remain a
connection.

You can check your follower count in your LinkedIn feed settings.

After that, you just need to post engaging content. Which is not necessarily
easy, but by monitoring your feed, and studying what’s working for others, you
can get a better idea of posting best practices. Here’s an overview of the most
shared LinkedIn posts of 2022.

In terms of spam detection - the focus of LinkedIn’s update - LinkedIn says that
its systematic updates have led to significant improvements in the detection and
removal of violative content, with the overall percentage of views on spam
declining by 7.3%.

So it’s improving its systems, while also providing some extra insight into the
workings of its algorithm.

You can read the full post on the LinkedIn Engineering blog.

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Filed Under: LinkedIn


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EDITORS’ PICK

 * Retrieved from Daniel Oberhaus/Wikimedia Commons on April 18, 2022
   Tracker
   
   
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   Now that the deal is done, we watch as the Musk-Twitter era begins.
   
   By Andrew Hutchinson and Emma Wiltshire • Nov. 2, 2022


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Read next
 * Retrieved from Daniel Oberhaus/Wikimedia Commons on April 18, 2022
   Tracker
   
   
   THE COMPLETE ELON MUSK–TWITTER SAGA
   
   For months, we’ve been tracking Elon Musk’s $44 billion deal with Twitter.
   Now that the deal is done, we watch as the Musk-Twitter era begins.
   
   By Andrew Hutchinson and Emma Wiltshire • Nov. 2, 2022

Latest in LinkedIn
 * LinkedIn Shares Insights into How its Feed Algorithm Works in Overview of
   Spam Tackling Efforts
   By Andrew Hutchinson
 * LinkedIn Shares New Insights into the Latest Tech Marketing Trends
   By Andrew Hutchinson
 * LinkedIn Expands its Company Commitments Display to More Surfaces
   By Andrew Hutchinson

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