The Impact of Short-Video Platform Algorithms on Social Aesthetics and Public Cognition

Abstract

In today's digital age, short-video platforms have become the dominant force in online consumption. With the seamless integration of technology and entertainment, they have attracted billions of users worldwide. The rapid growth in the number of these platforms is attributed to the complex algorithms that support content recommendation systems, which effectively customize user experiences based on individual preferences. However, this technological advancement raises profound questions about its broader impact on public perception and social aesthetics. This study investigates how public cognition and social aesthetics are affected by algorithms used by short-video platforms. To examine the standardization process of algorithmic aesthetics and the cognitive reshaping effect of immersive media design, it employs content analysis techniques and blends interdisciplinary ideas of communication studies, computer science, and cognitive psychology. According to studies, the platform's recommendation algorithm, which was developed using collaborative filtering and deep learning, homogenizes aesthetic preferences with the aid of a "tag system" and "imitation learning" mechanisms. In contrast, features like auto-play and infinite scrolling cause users' attention to become fragmented and rely on the algorithm. In the meantime, algorithmic traffic distribution exacerbates the cognitive dilemma of the country's broad entertainment trend and marginalizes specific aesthetics.