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基于 DNN 的跨媒体数据分析对大学生新媒体素养的影响研究。

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

机构信息

The Graduate Institute of Design Science, Tatung University, Taipei, Taiwan 11604, China.

School of Art and Design, Fuzhou University of International Studies and Trade, Fuzhou, Fujian 350200, China.

出版信息

Comput Intell Neurosci. 2022 Aug 3;2022:9224834. doi: 10.1155/2022/9224834. eCollection 2022.

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.

摘要

新媒体逐渐成为大学生依赖的主流媒体,新媒体也带来了颠覆性的变化,成为大学生获取和传播信息的必备媒介,如学习、人际交往和娱乐。年轻的大学生已经成为新媒体最热情的接受者和使用者。大学生需要具备识别、理解和批判新媒体的能力。新媒体素养已经成为每个生活在现代社会的大学生必须具备的基本素质。本文以 826 名大学生为研究对象,采用深度神经网络(DNN),分析他们的媒体选择倾向、媒体使用时间、积极影响以及与新媒体素养的关系。良好的新媒体素养的形成对大学毕业后的工作和学习有积极的影响和作用,使他们成为媒体社会的主力军。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f699/9365540/7a4e6e361ce0/CIN2022-9224834.001.jpg

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