摘要
用户对算法的感知是研究用户与算法关系的逻辑起点与现象基础。已有实证研究多分析用户对算法作用与影响的感知,而算法权力的感知机制尚未得到明确的实证探析。本研究基于“网络空间”“权力线索”和“权力感知”的理论联系,采用结构方程模型和中介效应检验,分析了社交媒体用户感知算法权力的路径机制。研究发现,用户藉由边界、功能及塑造三个维度感知到网络空间;在网络空间中又进一步感知“操纵”“掌握”“隐藏”与“监视”的权力线索,形成对算法权力的感知;同时认知惰性导致用户感知线索过程中出现了遮掩效应,进而基于算法权力线索形成了部分中介效应机制。本研究据此构建了“算法空间权力感知机制”,将对算法技术影响的感知分析拓展为对算法权力线索的感知分析,为研究用户感知算法提供了一套基于“算法-空间-权力”关系的解释框架。
Perceptions of algorithms by users constitute the logical starting point and foundational phenomenon for studying the relationship between users and algorithms. Existing empirical research often analyzes users' perceptions of the functions and impacts of algorithms,yet the mechanisms of perceived algorithmic power remain empirically underexplored. This study integrates theories of “cyberspace”“power cues” and “power perception”,employing structural equation modeling and mediation analysis, to examine the pathway and mechanism through which social media users perceive algorithmic power. The research identifies that users perceive cyberspace through dimensions of boundary, functionality, and shaping. Within cyberspace, users further perceive algorithmic power through cues of “manipulation” “control” “concealment”and “surveillance” while cognitive inertia leads to masking effects during the perception of these cues, thereby forming partial mediation mechanisms in perceiving algorithmic power cues. Based on these findings, the study constructs the theoretical framework of “Algorithmic Spatial Power Perception Mechanism”, expanding the analysis of algorithmic technological impact perceptions to include perceptions of algorithmic power cues. This framework provides an explanatory framework for studying user perceptions of algorithms based on the relationship among “algorithm”“space”and“power”.
作者
甘浩辰
陈彦西
Gan Haochen;Chen Yanxi(School of Public Administration,University of Electronic Science and Technology of China;School of Humanities,Chang’an University)
出处
《新闻界》
北大核心
2024年第7期36-48,62,共14页
基金
四川省哲学社会科学重点研究基地项目“算法技术影响下社交媒体用户互动行为与舆论生成机制研究”(QGXH23-10)。
关键词
算法感知
算法权力
算法空间
智能传播
algorithmic perception
algorithmic power
algorithmic space
intelligent col unication