To better understand how it works

It is necessary to understand the goals that allow users to spend the most time on the application. Therefore, in addition to an interface specifically designed to attract users, it is also necessary to provide each user with content that interests them and makes them see more. Algorithms for this purpose consider thousands of factors to classify content. It will store information about user activity to determine what content will ultimately be served to people in a certain order. How do algorithms classify content? At the end of the year, the platform announced that registrations, comments, likes, follows or reactions are the key points in classifying content on audience. However, since the last update in 2017, some of the main ranking factors include content, authentic posts, dynamic audience relevance, vertical formats. Additionally, as we mentioned earlier, there is no single algorithm that determines the order of importance of content. Instead, different sections have their own algorithms and processes that determine the best content for each user in each situation. Speaking of content, we recommend reading this article from the Influencer Marketing blog on The Complete Guide to Creating Branded Content.


How does the algorithm classify posts? Let's say users want to see posts from family members or closest friends first. Therefore, the first posts users see are always from the accounts they follow. To classify them, the algorithm will rely on hundreds of pieces of data called signals, such as who you follow, what you like, or who you've recently interacted with. It also takes into account other factors such as preferred formats. The other most important signals that form an important part of the app rating system are user activity. The algorithm checks all the posts we interact with, including the accounts you like, the topics you share, the posts you save or comment on. Information about the publication These signals are based on metrics related to the publication (number of likes, number of comments, number of saves, average views, engagement rate, etc.), but also on other statistics related to the context of the publication (date and time of publication, video length, location) . Information about the author of the post These signals are directly related to the relationship of the user to the account that published the content, the frequency and number of interactions, the history of the interaction of the user with the author of the post, etc. These signals allow an algorithm to better understand the user's interest in the content published by a particular account, the history of comments , interactions in the last weeks, likes and logins.


Get Active Database : Serbia Phone Number List


Based on these signals, the feeding algorithm will try to guessMeasure which posts are most likely to drive user interaction. Prioritize the likelihood that the user will perform one of the following five interactions Observe the publication for few seconds Save the post to favorites Comment on the publication Like Click on the profile As explained, in many cases the platform tries to avoid showing too many posts from the same person or showing too many many suggested posts in a row. How does the algorithm classify stories? The stories and ads people see on profiles correspond to the people they choose to follow. When organizing stories, the platform takes into account the following elements Viewing history Checks how often a user views the stories of a particular account. Interaction History Considers how often an audience has interacted with an account's stories, such as liking or sending direct messages. link To do this, check the relationship with the author of the story, including the likelihood that they are a friend or family member. Also read Increase engagement with these simple steps How does the algorithm classify posts on the Explore tab? The Explore tab is designed to introduce users to new content and brands.