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LinkedIn needs a measurement system to know how much time the user spends reading a publication, in order to judge its quality. But before delving into what Dwell Time Linkedin is, a quick reminder of how the algorithm works is in order! LinkedIn algorithm reminder of the basics LinkedIn creates a personalized feed based on each user. It is based on the behavior of the latter, the company pages and hashtags followed or the nature of the relationships he maintains with his contacts. First of all, the LinkedIn algorithm prioritizes your professional connections and relationships.You may follow Bill Gates on LinkedIn, but what are the chances that you are constantly interacting and communicating with each other? Very weak unfortunately!.
Therefore, if the social network will sometimes show you the billionaires publications, it Albania WhatsApp Number will still give priority to your colleagues and contacts with whom you interact regularly. And to do this, it analyzes the comments, likes and shares that you have previously left. Over the past two years, LinkedIn algorithm updates have resulted in more than a increase in viral activity. Proof that it works! In order to go even further in the user experience, LinkedIn has just added to its criteria, the reading time of a publication, also called Dwell Time. How does Dwell Time improve LinkedIn News Feed? Dwell Time refers to the time spent on a publication. Following tests available on LinkedIns .

Engineering blog , the social network realized that the more time an Internet user spends on a post, the more likely they are to engage dwell time linkedin what is it To improve this criterion, LinkedIn went further by looking for a time threshold allowing it to be deduced that publications are skipped. And yes ! After how many seconds of reading can content be deemed relevant? If there is no exact answer, the professional social network based itself on Bayes theorem to optimize its Dwell Time. Which gives this formula be careful of the headache! dwell time and bayes theorem Bayes theorem states conditional probabilities. The LinkedIn algorithm is therefore based on the probabilities that a user.
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