Updating the Gatekeeper in the New Media Age: The Algorithm

In the era of new media, an algorithmic recommendation mechanism is widely used by social media platforms as a new type of gatekeeper and has greatly affected people's entertainment methods and habits. Algorithms collect and analyze user data and then recommend similar content to users based on relevant tags and keywords. Although this provides users with a personalized experience, this personalized service unconsciously forms an information cocoon, which can easily limit people's cognition. It is the purpose of this article to let the audience understand the impact of the algorithmic recommendation mechanism and to reduce the harm to the audience's cognition under the algorithmic recommendation mechanism. Through reading and citing various literature studies, this paper clarifies the theoretical positioning of algorithmic recommendation mechanisms in gatekeeper theory and enumerates the positive impact of algorithmic recommendation mechanisms on individuals, social media platforms and society along with the development of social media platforms, as well as the negative impact on individuals and society. Finally, through the negative impact of the algorithmic recommendation mechanism, this paper discusses how to break the information cocoon room and reduce the negative impact of the algorithmic recommendation mechanism on the audience's cognition from three dimensions: individual audiences, mainstream media, and social media platforms.