摘要
算法技术深度介入新闻业并挑战新闻认识论。本文引入“认知基础设施”视角,重新理解算法意图机制对新闻认识论的数字更新问题。通过对热搜和推流算法的考察,研究发现:算法的数据流塑造了快速、精粹的知识,它与新闻认识的可供性一起在操作与认知、可做与可知等不同层面衍生出复杂的认知竞赛。算法更新了新闻的知识形式,推进了“以流为新”和“视流如常”两种取向,但中国新闻业特殊的语境,使得数据知识不均衡地渗透着基于专业价值的公共知识。本文进而提出“新闻游渗”的观点,尝试打开对新闻的另一种认识。
Algorithm technologies have deeply intervened in journalism,challenging its epistemology.This paper introduces the perspective of"epistemic infrastructure"to reconceptualise the digital renewal of news epistemologies by algorithmic intentional mechanisms.Through an study of"Hot search"and"Personalized recommendation",the paper finds that algorithmic data streams shape fast and extracted knowledge,which,along with the availability of news awareness,creates a complex cognitive race between the operational and the cognitive,the doable and the knowable.Algorithms update the form of news knowledge,advancing both"streaming as new"and"streaming as usual"orientations,but the particular context of Chinese journalism makes data knowledge unevenly permeate public knowledge based on professional value.The paper further proposes the concept of"news osmotaxis"in an attempt to provide a new understanding of journalism.
出处
《新闻大学》
北大核心
2025年第9期32-47,117,118,共18页
Journalism Research
关键词
新闻认识论
认知基础设施
数字流通
推荐算法
算法认知
journalism epistemology
epistemic infrastructure
digital circulation
recommendation algorithm
algorithm cognition
