Trend Following: How Content Prototypicality Drives Liking on TikTok
(A2023-114114)

AUTHORS

Marc Bravin, University of Lucerne; Melanie Clegg, Vienna University of Economics and Business; Reto Hofstetter, University of Lucerne; Marc Pouly, Lucerne University of Applied Sciences and Arts; Jonah Berger, University of Pennsylvania

ABSTRACT

In the ever-changing social media world, trends are emerging on a daily basis making it easy for content creators to adopt an already successful type of content. However, it is not clear how closely content creators should follow the trend. In this research, we investigate how content prototypicality versus atypicality influences the success of trend-following videos. We argue that higher prototypicality increases liking. However, this effect occurs less strongly when users are less aware of the trend or when they can memorize the trend less. We investigate 57,060 TikTok dance videos using machine learning and regression analysis and demonstrate that prototypicality increases the number of likes. As expected, this effect is more pronounced the more users have been exposed to the trend and the more memorable the trend is. These findings are relevant for content creators and brands aiming at maximizing their contents’ engagement.