The debate over Real-time vs Algorithmic Timeline continues, as Instagram claims that the changes to algorithmic feed it made in 2016 has been effective, despite criticism from some users on the platform.
Algorithmic Timeline uses machine-learning to understand users interest as they interact with the platform, meaning the more you use it, the more accurate the suggestions will get over time. While real-time update means the natural flow of conversation which is supposed to be spontaneous, and thereby requires that you'll have to follow all conversations one at a time.
Albeit, the real-time update makes it rather too burdensome to collect on the information that matters to you, which is the reason the algorithmic timeline is preferred above it.
Algorithmic timeline favored posts that people cared for the most, based on past interactions, rather than the recent posts at the top of its feed. But just how does Instagram classify "relevance" or what are the ranking algorithm that is employed to decide what falls under the category?
There are fears about the possible abuse of the feature, as a monetization scheme, as the company may want to offer paid access for brands that are looking for targeted advertising.
Instagram is purported to favor a post, if it thinks something in it will matter to you based on your past interactions on similar content. While the analysis is based on machine learning of the content in the post, with timely posts prioritized over older posts.
The company, however denied any plans to offer paid access to brands that are looking for targeted advertising, stating that it won't down-rank users post in favor of advertisements, but if they post several items it may swap the important ones between the different posts.
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