算法推荐在“网络舆论审判”形成中的作用机理研究

Research on the Mechanism of Algorithm Recommendation in the Formation of “Internet Public Opinion Trial”

摘要: 随着算法推荐成为社交媒体信息分发的核心机制，其在提升信息获取效率的同时，也带来了“信息茧房”与“认知极化”等结构性风险，并对公共舆论形态产生了深远影响。本研究旨在系统阐释算法推荐机制如何通过强化信息茧房与加剧认知极化，从而在“网络舆论审判”的形成、传播与放大过程中扮演关键角色。本文的核心贡献在于，揭示了算法推荐并非中立技术工具，而是作为“结构性加速器”和“扭曲性放大器”，系统性地改变了舆论审判的规模、速度与强度，对司法权威、个体权利与社会共识构成了严峻挑战。最后，论文从算法伦理、平台治理与媒介素养教育等维度提出了规制与反思路径。

Abstract: As algorithmic recommendation becomes the core mechanism for information distribution on social media, it not only enhances the efficiency of information acquisition but also introduces structural risks such as “information cocoons” and “cognitive polarization”, profoundly influencing the formation of public discourse. This study aims to systematically elucidate how algorithmic recommendation mechanisms play a pivotal role in the formation, dissemination, and amplification of “online public opinion trials” by reinforcing information cocoons and exacerbating cognitive polarization. The core contribution of this paper lies in revealing that algorithmic recommendation is not a neutral technological tool, but rather functions as a “structural accelerator” and a “distorting amplifier”. It systematically alters the scale, speed, and intensity of public opinion trials, posing serious challenges to judicial authority, individual rights, and social consensus. Finally, the paper proposes regulatory and reflective pathways from the dimensions of algorithmic ethics, platform governance, and media literacy education.