算法推荐机制下公众媒介素养的延伸与挑战  

The Extension and Challenge of Public Media Literacy under Algorithmic Recommendation Mechanisms

作　　者：孙鹏飞 尚琴 陶靖 SUN Peng-fei;SHANG Qin;Tao Jing(School of Communication,Anqing Normal University,Anqing Anhui 246133,China)

机构地区：[1]安庆师范大学传媒学院,安徽安庆246133

出　　处：《齐齐哈尔大学学报（哲学社会科学版）》2023年第7期127-131,共5页Journal of Qiqihar University(Philosophy & Social Science Edition)

基　　金：安徽省高校优秀青年人才支持计划重点项目(gxyqZD202206);安徽省高校重点科研项目:算法推荐与主流意识形态建设(2022AH051007);安徽省研究生教育质量工程项目:新闻与传播专业学位新闻传播伦理与法规教学案例库(2022zyxwjxalk135);安庆师范大学“敬敷育英”创新创业引领计划重点项目:异化的话语权:集合行为下的未成年人网络暴力事件的信息传播与治理研究(2022JFY005)。

摘　　要：在媒介智能时代的广泛应用与推广下,算法推荐机制成为人们社会生活各领域中必不可少的科技伴侣。算法推荐一方面让用户可以全方位地接受信息带来的巨大便利,另一方面算法推荐的到来也产生了较多弊端胁迫着公众的生活。本文立足于我国公众的算法素养,以“媒介素养”为理论依据,在揭开算法推荐负效应的基础上探讨媒介素养如何延伸成为算法素养,以及在算法推荐机制下提升公众媒介素养提出相应的策略,帮助公众更好地抵挡技术对于个体所产生的负面影响。With the widespread use and promotion of the media intelligence era,algorithmic recommendation mechanisms have become an essential technological companion in all areas of people's social life.On the one hand,algorithmic recommendations allow users to receive information with great convenience in a comprehensive manner,but on the other hand,the arrival of algorithmic recommendations has also created more disadvantages that threaten the lives of the public.Based on the theoretical basis of media literacy",this paper explores how media literacy can be extended to become algorithmic literacy based on uncovering the negative effects of algorithmic recommendations and proposes corresponding strategies to enhance public media literacy under the mechanism of algorithmic recommendations,to help the public better resist the negative effects of technology on individuals.The study also proposes strategies to enhance public media literacy under the algorithmic recommendation mechanism,to help the public better resist the negative effects of technology on individuals.

关 键 词：算法推荐 算法素养 媒介素养 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术] G206[自动化与计算机技术—计算机科学与技术]