Short Video Audience Identification Data Recommended by Multiple Neural Network Algorithms

Abstract

Short Video is a hot new media in recent years. It has broad prospects for development, and the users are increasing rapidly. Therefore, it is significant to research and analyze mobile and audience identification data. Now, it is the Internet age, we get the useful information by collecting a large number of user behavior records. Traditional media platforms have problems such as serious information overload or slow transmission speed. So, in the big data era, how to generate interest in the short video industry through the analysis of precise audiences has become an urgent problem to be solved. The authors use survey and audience identification data recommended by multiple neural network algorithms to analysis. The research shows that the young and middle-aged people are mainly users and producers. The users’ interest, high-quality educational content and entertainment are the potential factors affecting the popularity of video. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.