信息资源管理学报 ›› 2024, Vol. 14 ›› Issue (5): 91-103.doi: 10.13365/j.jirm.2024.05.091

• 研究论文 • 上一篇    下一篇

平台可供性视角下算法的嵌入与可见机制研究

杜燕1 谢新洲2   

  1. 1.北京工商大学语言与传播学院,北京,102445;
    2.北京大学新媒体研究院,北京,100871
  • 出版日期:2024-09-26 发布日期:2024-10-15
  • 作者简介:杜燕,博士,讲师,研究方向为智能传播,网络消费行为与心理;谢新洲(通讯作者),博士,教授,博士生导师,研究方向为新媒体与网络传播、媒介经营管理、竞争情报与企业战略竞争等,Email:xzxie@pku.edu.cn.
  • 基金资助:
    本文为国家社会科学基金重大项目“中国特色网络内容治理体系与监管模式研究”(18ZDA317)研究成果之一。

Research on Algorithm Embedding and Visibility Mechanism:A Platform Affordance Perspective

Du Yan1 Xie Xinzhou2   

  1. 1. School of Languages and Communication, Beijing Technology and Business University, Beijing,102445;
    2. School of New Media, Peking University, Beijing, 100871
  • Online:2024-09-26 Published:2024-10-15
  • About author:Du Yan, Ph.D., lecture, research interests: intelligent communication, online consumer behavior and psychology; Xie Xinzhou (corresponding author), Ph.D., professor, doctoral supervisor, research interests: new media and internet communication, media operation and management, competitive Intelligence and strategic competition of enterprises, Email: xzxie@pku.edu.cn.
  • Supported by:
    This article is one of the research results of the Major Project "Research on the Governance System and Regulatory Model of Internet Content with Chinese Characteristics"(18ZDA317), funded by the National Social Science Foundation of China.

摘要: 鉴于算法相关性的日益增强,如何落实平台的主体责任成为焦点问题。本研究基于可供性的理论视角,通过混合研究方法,分析了算法技术、平台环境与用户感知之间的关系,以明确平台在其中的作用以及出现的问题。研究结果显示,算法通过特定的编码程序、多目标优化以及百亿级别的特征向量组合,重塑了平台环境;面向普通用户,算法具有不可见性、不可编辑性和不可访问性,平台通过信息线索、界面设计和功能设置初步构建了算法的可见机制,但效果有限。本研究结合算法的嵌入逻辑为促进用户算法知情提供对策建议,具有理论与实践意义。

关键词: 算法推荐, 网络内容平台, 平台可供性, 感知可供性, 算法知情

Abstract: Given the increasing relevance of algorithms, how to implement the main responsibility of platforms has become a focal issue. Based on the perspective of affordance theory, the study analyzes the relationship between algorithms, the platform environment, and user perception through mixed research methods to clarify the role of platforms in the process and the problems that arise. The research results show that the algorithm reshapes the platform environment through specific encoding programs, multi-objective optimization, and billions of feature vector combinations. For ordinary users, the algorithm is invisible, uneditable and inaccessible. The platform initially constructs the visibility mechanism of the algorithm through interface cues, but the effect is limited. The research, combined with the embedding logic of the algorithm, provides policy recommendations to promote user algorithmic knowledge, which has certain theoretical and practical significance.

Key words: Algorithm recommendation, Web content platforms, Platform affordance, Perceived affordance, Algorithmic knowledge

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