Research on the Influence of DNN-Based Cross-Media Data Analysis on College Students' New Media Literacy

基于深度神经网络的跨媒体数据分析对大学生新媒体素养影响的研究

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Abstract

New media has gradually become the mainstream media that college students rely on, and new media has also brought about subversive changes and has become an essential medium for college students to receive and disseminate information, such as learning, interpersonal communication, and entertainment. Young college students have become the most enthusiastic recipients and users of new media. College students need to have the ability to recognize, understand, and criticize new media. New media literacy has become the basic quality that every college student living in modern society must have. This paper takes 826 college students as the research object with deep neural network (DNN), and then analyzes their media selection tendency, media usage time, positive influence, and the relationship with new media literacy. The formation of good new media literacy has a positive effect and influence on the work and study after the university, making it the main force of the media society.

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