As technology of mass media advances, so do the audience’s expectations. Users of social media now expect the suggested content to be specifically targeted to their preference. The modern user has a decreased attention span of just 8 seconds and will quickly click away if not significantly engaged. (He, 2021) As competition increases, platforms, which run on revenue generated by engagement, have utilized AI to populate feeds with perfectly targeted, personalized content.


A perfect cutting-edge example of this is TikTok’s breakthrough technology, which uses advanced AI algorithms to learn user preference.  With Tik Tok, it’s simply plug and go. No UI questionnaires, no need to friend or follow, or even “like” content.   TikTok has pioneered a new methodology that uses an ever-changing algorithm to decide what their users consume. It is a rapid, hyper-efficient matchmaker. (Wei, 2020) Merely by watching some videos, you can quickly train TikTok to identify what you like or in other words, while you watch TikTok, it watches you.  AI completely powers the TikTok platform. A spokesperson for Bytedance, TikTok’s parent company, stated, “We build intelligent machines that are capable of understanding and analyzing text, images and videos using natural language processing and computer vision technology.”  According to Wei, “its algorithm is so efficient that its interest graph can be assembled without imposing much of a burden on the user at all. It is passive personalization, learning through consumption” (Wei, 2020). As Forbes writer Tauli chimes in, “We’ve all gotten so caught up in maximizing reach by growing a massive fan base through subscribers or followers, so it’s refreshing to have a platform with an algorithm that rewards content above all else.” (Tauli, 2019)  Others have stated it is the wave of the future.

The apps algorithmic brilliance continues with its ability to keep these distinct subcultures, with their different tastes, separated.  TikTok has been called the Sorting Hat from the Harry Potter universe. For, just as that magical hat sorts students at Hogwarts, TikTok’s algorithm sorts its users into dozens and dozens of subcultures”. (Wei, 2020) This is a very important attribute to the apps success because if one culture starts to dominate an app it can cause other cultures to leave. Many say a contributing factor for the downfall of MySpace was due to an influx of HipHop artists who dominated the landscape. (Ingram, 2010) This algorithm eliminates that possibility.

The overall success of TikTok is clearly shown when looking at research done by Statista in 2019.  TikTok, it appears, is exceptionally good at recommending content, so much so that when a user opens the app, on average they will stay in it for over 10 minutes, more than three times longer than the 2.9 minutes spent on Instagram. (Statista, 2021) This demonstrates that the algorithms-based recommendations threaded throughout TikTok are highly effective at matching user preference to desired content.


Societal expectation of media will change and evolve in tandem with technology. Advanced algorithms, which can independently identify and accommodate user preference while delineating subgroups, are bound to be part of the way the media begins to meet the demands of its audience.  These intelligent intuitive algorithms will soon escape the bounds of TikTok, then trickle out of social media.  Can you imagine that level of hyper-efficient interest matching applied to other opportunities and markets?  Will we ever be able to put our devices down?


Eugene Wei, a renowned software engineer and self-appointed cultural determinist shared a story in his blog which shows the far reach this type of algorithm may have on society.  He was invited to visit the Newsdog office in Beijing. Newsdog was, at the time, the number one news app in India.  All the stories in Newsdog were selected algorithmically, explained the CEO.  Wei looked through the stories, all in Hindi, and then looked at the office filled with about 40 Chinese software engineers, tapping away at their computers, then scrolled through page after page of Hindi stories in the app. “Wait,” Wei asked. “Do you have people in this office or at the company who know how to read Hindi?” The CEO just looked at him with a smile. “No,” the CEO of Newsdog said. “None of us can read any of it.” (Wei, 2020) 

It has long been prophesied that the world would speak a common language which would allow us to communicate with ease.  Behold, the algorithm.

He, B. (2021). Social media multitasking could affect attention span. 

Ingram, M. (2010, July 16). Is the difference between Myspace and Facebook Black and white? Gigaom.

Reverse engineering how TikTok algorithm works. Veed. (2019).

Statista. (2021, July 6). Top U.S. mobile social apps by session length 2019. Statista. 

Taulli, T. (2020, February 3). Tiktok: Why the enormous success? Forbes.  

Wei, E. (2020, August 11). Tiktok and the sorting hat. Remains of the Day.