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TikTok (Previously known as Musical.ly) is a social media app on Apple and Android devices for short video creation, sharing, and discovery. Teens and adults use the app to express themselves and make videos which they then share with others across the globe. The original Musical.ly app allowed users to choose from different music and dialogue, with which they could lip-sync and make funny or entertaining videos to share. What drove the app’s popularity even further was that content creators often shared their creations on more popular social media sites at the time, such as Instagram and Facebook.
It was not until 2018 that Musical.ly was acquired by a Chinese company called ByteDance and rebranded as TikTok. At the time, TikTok had 500 million users, which grew to 1 billion by 2022 and now rivals Instagram and other massive social media sites. According to Wall Street Journal, Facebook and Instagram have seen a decline in engagement on their platform, while TikTok has seen increased engagement.
Instagram’s push to mimic TikTok with the introduction of Instagram Reels hasn’t quite been a success. Wall Street Journal states that Instagram users spend less than one-tenth of the hours TikTok users spend watching videos daily. This means that Meta has to catch up to capture the market again.
One of the main reasons TikTok has become the platform of choice for teens is that it allows content creators to monetize their content and earn money from their videos. This was something that Instagram did not offer and is an important factor in why teens prefer interacting and growing their fan base on TikTok compared to Instagram.
That being said, a big part of TikTok’s success can be attributed to its innovative use of artificial intelligence and machine learning technologies designed to push personalized content to its viewers and its divisive strategies created through data analytics and big data analytics.
Like other social media platforms like Facebook and Instagram, TikTok’s algorithm employs machine learning to determine what kind of content a user is most likely to engage with and then show them more of it by locating similar videos popular among others with similar tastes. This technique is highly effective and is typically seen on other video sites like YouTube and Netflix.
The ‘For You’ feed in the TikTok app is a central feature of the TikTok platform. The ‘For You’ feed is designed to make your TikTok experience personal. This feed is curated through multiple algorithms, all working together to provide a personalized experience.
A little less known fact about TikTok is that the app is a gold mine regarding the user data it collects. When you create an account on TikTok, the app collects data about your activities and preferences based on the videos you watch as well as other types of data such as the device you are using, your location, IP address, information about devices connected to your WiFi network even if TikTok isn’t installed on them, your search history, the content of your messages, what you are viewing and for how long.
In addition to this, It also collects device identifiers to track your interactions with advertisers. In short, this app is probably the most intrusive app you can install on your device.
This aggressive data harvesting employed by them makes TikTok a huge success for advertisers. With the vast amounts of data available to them, they can serve tailored ads based on videos that a user has watched and liked. Capturing sentiment with this level of accuracy is a lot more difficult on other platforms.
By utilizing prescriptive analytics, TikTok uses the data collected to determine an appropriate course of action. This is accomplished by looking at all the relevant factors and then analyzing the data, which will yield recommendations for the next step. This form of analytics plays a vital role in enabling TikTok to make data-driven decisions which, in most cases, will facilitate successful decision-making.
Often, machine learning algorithms are employed with prescriptive analytics to process large amounts of data faster and make recommendations based on a specific combination of requirements. This is especially important in the case of TikTok, as they deal with huge amounts of data.
For example, if a user watches a video until the end, the algorithm automatically notices this engagement and sees that you like this content. Videos are then ranked to determine how likely you will be interested in each video and delivered to each unique ‘For You’ feed.
According to TikTok, the ‘For You’ feed is powered by a recommendation engine designed to deliver personalized lists of suggested videos tailored to the user. The recommendations are based on numerous factors such as (TikTok, n.d):
- User interactions – This includes the videos you liked or shared, the accounts you follow, the comments you post, and the videos you create.
- Video information, such as captions, sounds, and hashtags.
- Device and account settings, like your language preference, country setting, and device type.
These factors are processed by the recommendation algorithm and weighted based on their value. The more you engage with videos on the app, the more personalized your recommendations become.
Why is TikTok more addictive than other platforms?
Unlike other social media platforms which rely on a user’s active online behaviors such as their ‘Followings’, ‘Friends’ and ‘Likes’ to gauge their preference, TikTok’s powerful recommendation algorithm captured and used users’ passive and subtle behavioral patterns to teach its algorithms about the user in real-time, as they’re watching.
Sometimes a user may spend more time watching a certain type of video but don’t hit the like button. The algorithm notes this data, and the user is fed more of this data. In a way, the user is interested in this type of content but maybe didn’t quite like this specific video.
All these subtle interactions are recorded and passed onto the algorithm to carefully curate the user’s feed. This hyper-responsive approach of their recommendation system thus allowed users to be completely passive and still receive an engaging, personalized feed much faster than they would on any other platform.
TikTok’s approach relieves the user of having to build an audience to have a chance of getting famous. The purpose of this approach and why it is so effective is that it does not rely on people’s social activity, such as having followers or following anyone else, to recommend engaging content. Instead, it ranks content for its quality and gives even a brand-new user a chance to go viral as long as their video is entertaining enough.
Controversies Surrounding TikTok’s Algorithms and Data Practices
This popular short-form video app has recently been the subject of many controversies due to various issues related to its algorithms and data practices. One major concern is data privacy, as the app has been criticized for collecting and sharing user data with third parties, including the Chinese government. The app is sometimes referred to as ‘spyware’ due to the aggressive amounts of data it collects from the user.
Furthermore, there have been national security concerns regarding the app, as a Chinese company owns it, leading to bans or restrictions in several countries over fears that the app could be used for espionage or influence operations. Some countries, such as India, have taken extreme measures and banned the TikTok app in their country.
TikTok was also temporarily prohibited in the US and forced to divest its US assets to an American company which it did. The app was after that allowed to operate in the US. In 2023, the US banned TikTok on all federal government devices due to growing security concerns.
Conclusion
In conclusion, TikTok’s machine learning algorithm plays a crucial role in determining what content is shown to users, but it also raises several controversies. Data privacy concerns, content moderation issues, national security concerns, child safety, and mental health concerns. While TikTok is a popular and entertaining platform, it’s important to be aware of these controversies and to consider the potential implications of using the app.
As the platform continues to grow and evolve, it will be important for the company to address these concerns and ensure that the algorithm is transparent, and accountable, and respects the user’s privacy and well-being.
