28 May 2021 714 words, 3 min. read

Here is the most crucial factor for the virality of your LinkedIn posts

By Pierre-Nicolas Schwab PhD in marketing, director of IntoTheMinds
After discussing the effect of emojis and the word count on the virality of LinkedIn posts, it’s time to reveal THE factor that crushes all others. This factor accounts for 1/3 of the success of your LinkedIn posts. So, you should take the time to […]

After discussing the effect of emojis and the word count on the virality of LinkedIn posts, it’s time to reveal THE factor that crushes all others. This factor accounts for 1/3 of the success of your LinkedIn posts. So, you should take the time to read the research results I just conducted on 4.6 million LinkedIn posts in 193 countries.

I obtained the unpublished results presented here thanks to data made available by Linkalyze. They were prepared and analyzed using the Anatella and Modeler solutions from TIMi.

The results in a nutshell

  • the number of connections of a LinkedIn user explains 34% of the virality of his posts
  • a user with 24000 connections has 3x more chances to reach 100 reactions on a post than a user with 4000 connections
  • 51,12% of the posts are published by people with less than 1442 connections
  • the probability of reaching the 100 reactions threshold on a LinkedIn post increases by 1% with each additional 500 connections

A reminder of how to analyze the virality of LinkedIn posts

A quick reminder about the results already published is necessary.

I first showed here that there are essential differences in engagement on LinkedIn depending on the language and the country. It seems statistically more difficult to get comments or likes on a post in French than in Swedish or Portuguese.

The statistical modeling then shows that 2 factors play a role in the virality of a LinkedIn post:

  • the number of words: the more the number of words increases, the more the probability to reach the 100 reactions threshold (like + comments) increases
  • the number of emojis: emojis have an effect distinct from the number of words, and 16-18 emojis seem to be optimum to reach the 100 reactions threshold on LinkedIn.

These 2 factors do not have the same weight. The number of words “weighs” 19.1% in reaching the 100 reactions threshold, emojis 2.4%. But a 3rd factor weighs for 34% …

The effects of network size on the virality of LinkedIn posts

The variable that dominates all others to explain the virality of a post on LinkedIn is the number of connections. Simply put, the more connections you have on LinkedIn, the more likely you are to reach the 100-reaction mark.

network size effect on linkedin post reach

With a network of 4000 connections, the probability is about 6%. With a network of 24000 people, it is 18%. In other words, going from 4000 to 24000 connections allows multiplying by 3 the probability of reaching 100 reactions on LinkedIn.

However, 51.14% of the content on LinkedIn is put online by users with less than 1442 connections. This gives you an idea of their chances to see their publications go viral.

As you can see on the graph, the relationship is linear from 4000 connections. For every fraction of 500 additional connections, the probability of your LinkedIn post reaching 100 reactions increases by 1%.


To fully understand the results of this analysis, it is essential to understand the methodology.
First of all, the results are based on an essential element. I modeled the probability of a LinkedIn post reaching 100 likes. Why 100 likes? First, I only managed to do it once in 15 years, and second (more factually) because +/-3% of LinkedIn posts reach this threshold.

data preparation Linkedin dataset Anatella

I won’t go into detail about the preparation of the data. However, you should know that it was realized using Anatella (see diagram below), a tool that I already talked about for its positive points, especially its ability to process large amounts of data quickly.

screenshot anatella : effect of network size on linkedin virality

Reaching 100 reactions is, therefore, an impressive feat. With TIMi’s Modeler tool, I defined a binary variable (reach threshold / not reach threshold) and analyzed the variables that played a role in the final result.

The screenshot above shows you the results as presented in the report generated by Modeler from TIMi. You can see that only 3 variables are “discriminating” (i.e., they have a statistically significant effect). The “subscribers’ profile” variable (the number of connections) explains 34% of the observed effects. Therefore, its impact is more significant than that of the number of words and the number of emojis combined.


If you want to increase your visibility on LinkedIn and your chances of going viral, there are no 50 solutions: you need to increase the size of your network. In other words, you have to invest time in adding new connections to your network. This task is not easy because the number of invitations is now limited to 100 per week.

Posted in Data & IT.

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