大数据“杀熟”语境下的媒介重构——基于消费者的“再驯化”现象

Media Reconstruction in the Context of Big Data “Killing Ripe”—Based on the Phenomenon of “Re-Domestication” by Consumers

摘要: 本文以大数据“杀熟”为背景，结合传播学驯化理论、符号双轴理论及拟态环境理论，探究电商平台算法与消费者的互动逻辑。研究表明，电商平台借算法打破符号双轴平衡，通过组合轴编排商品展示、聚合轴筛选用户标签，构建拟态消费环境，导致消费者决策权旁落、主体异化。为应对算法“反向驯化”，消费者通过组合轴关键词重置与功能跨界搜索、聚合轴数据身份伪装、亚文化编码与“反向种草”等“再驯化”行为反制。但二者博弈存在不对等性，算法迭代快、平台控场力强，消费者“再驯化”易陷“数据陷阱”，且平台隐私滥用引发伦理争议。研究认为，人与技术为双向博弈，需以算法可解释性平衡技术效率与人文关怀，规范算法应用以保障消费者权益，避免“两败俱伤”，推动数字消费生态健康发展。

Abstract: Against the backdrop of big data “killing ripe” (a phenomenon where e-commerce platforms charge regular customers higher prices through algorithms), this paper explores the interaction logic between e-commerce platform algorithms and consumers by integrating the Domestication Theory, the Theory of Syntagmatic and Paradigmatic Axes of Symbols, and the Mimic Environment Theory from the perspective of communication studies. The study shows that e-commerce platforms use algorithms to break the balance between the syntagmatic and paradigmatic axes of symbols. They arrange the display of commodities through the syntagmatic axis, screen user tags through the paradigmatic axis, and construct a mimic consumption environment, which results in the sidelining of consumers’ decision-making power and the alienation of consumers as the main body of consumption. To respond to the “reverse domestication” by algorithms, consumers carry out “re-domestication” actions for countermeasures: on the syntagmatic axis, they reset keywords and conduct cross-functional searches for commodities; on the paradigmatic axis, they disguise their data identities; besides, they use subcultural coding and “reverse seeding” (a practice where consumers share negative experiences of products despite giving high ratings to reveal the true nature of commodities). However, there is an imbalance in the game between consumers and algorithms: algorithms iterate rapidly, platforms have strong control over the scenario, consumers’ “re-domestication” actions are likely to fall into the “data trap” set by platforms, and the abuse of consumers’ privacy by platforms gives rise to ethical disputes. The study holds that the interaction between humans and technology is a two-way game rather than one-sided suppression. It is necessary to take algorithm interpretability as a breakthrough to balance technological efficiency and humanistic care, standardize the application of algorithms to protect consumers’ rights and interests, avoid a “lose-lose” situation, and promote the healthy development of the digital consumption ecosystem.