The algorithm looks at the engagement rate of this sample, that is, the rate of people who like and comment. This initial rate is essential because it largely influences the final reach of the post. Or rather the opposite: the algorithm believes that if there is no strong initial engagement, the content is not relevant. It is said to be measured between the first hour and the first three hours of the content's life.
Based on this initial engagement rate, the algorithm expands the poland whatsapp mobile phone number list audience by giving priority to people in your network , but especially to people in the network of those who have engaged on your post, considered “similar profiles”, who could therefore be interested in your content. (Yes, we tend to appreciate the same things as the people around us, culture, the network, so we feel similar emotions on similar content).
If the engagement rate continues to be similar, the post continues to grow in number of views . This is what allows content with a high engagement rate to go viral.
There is one important criterion to take into consideration:
As you might imagine, posting a comment is an act that requires much more involvement than a like.
They don't have the same "emotional weight" at all and therefore don't have the same weight for the algorithm. I would say the ratio is between 10 and 20 (1 comment = 10-20 likes).
Other Factors That Go Into LinkedIn's Algorithm
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We can say that the engagement rate far exceeds all other criteria for the distribution of a publication.
However, some other criteria can influence (especially downwards) the reach of a post:
The number of hashtags used . The hashtag is like a “category” of the post for LinkedIn. If there are none, the algorithm cannot classify it. If there are too many, it will consider it excessive and try to make it appear in all categories.
Network Size : While this may seem to have very little effect, it would appear that the size of your network may play a role in the initial sample size of the post. (A study is planned to either disprove or confirm this hypothesis.)
Readability : A LinkedIn view is just someone who passes by your post, without necessarily stopping. If your post is not readable, the likelihood of engagement is very low.
Views on your latest publications. If your latest posts have had a lot of views, LinkedIn will tend to enlarge the initial sample, considering that the quality of the post is more likely to be good.
Outbound Links. As we said, LinkedIn wants to keep users on the network to monetize them. Including outbound links from LinkedIn in posts increases the likelihood that the user will leave LinkedIn. Publications that contain an outbound link are therefore devalued.
Conclusion of the article
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Because the LinkedIn algorithm is a black box, these explanations are based on observations made by the LinkedIn community over time. The algorithm is likely to evolve, and the influence of certain criteria remains unknown…
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