Is TikTok is unique and unusual because it’s the only Chinese social platform with international exposure, and an appeal that encapsulates the Western world? Or is it because of the concepts and mechanism?
Either ways, Millennial and Gen-Z especially long for micro-entertainment and they love TikTok. This makes to the list of TikTok’s defining appeals. Videos are fun and interesting, short, and stylish.
TikTok allows its users to follow other accounts and create a feed of new and diverse content from the creators they follow or enjoy the most. The “For You” feed on TikTok shows diverse content from users that you wouldn’t normally consider following. Perhaps it’s another reason why users find TikTok appealing. The app allows everyone – even the users with few followings – to “go viral” and become stars overnight.
The app has introduced many regular users to stardom. Take Baby Ariel (Ariel Martin) and Loren Gray for instance, who joined Musical.ly in 2015 and are now the most-followed users on TikTok with over 40 million followers.
That’s insane! Fancy using TikTok for marketing your small-scale startup.
Now, What About the Algorithms?
Similar to other social media platforms and applications, TikTok feeds were engineered using a recommendation algorithm that uses an array of tools and factors to customize it for each user.
The recommendation algorithm for TikTok is designed around input factors. It works in a manner similar to how YouTube measures and tracks user interaction.
The recommendations a user is served are based on how a user interacts with the app, and that includes following a particular account or posting a comment. If you only follow humorous comedy-related accounts, and solely double tap to like or comment on videos related to comedy then that is what your TikTok recommendation will be.
This is how TikTok’s algorithm infers what a particular user is really into and personalizes the feed based on those gatherings.
But user interactions are just one aspect of an entire equation. TikTok notes that the video data – which may contain details including captions, sounds, or hashtags – and devices, or sign in settings also play a role in what appears on your feed. Language choice, country settings, as well as the type of device a user uses also factors in ensuring “the system is optimized for efficiency.”
However, in comparison to other data points, device and account settings receive lower weight in the recommendation system as users don’t actively express these as preferences.