算法巡逻内容:危害在哪里?

Q1 Social Sciences
Monica Horten
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引用次数: 0

摘要

本文的核心是对“影子禁令”这一通俗概念的考察。它揭示了Facebook平台上的算法在没有明确针对内容进行删除的情况下抑制内容分发的方式,并检查了由此导致的对用户言论的扼杀。它揭示了Facebook影子禁令是如何通过阻止新闻推送内容的传播来实施的。决策标准基于“行为”,这是一个与通过数据模式识别的页面活动相关的术语。这是一种植根于计算机安全的技术,它提出了关于安全和言论自由之间平衡的问题。本文研究的是网络平台内容审核责任问题。该研究研究了2019年11月至2021年1月期间20个英国脸书页面的影子禁令经验。使用人权标准和从Facebook Insights数据中产生的比较指标来评估潜在危害。实证研究与最近的立法进展有关:欧盟的《数字服务法案》和英国的《在线安全法案》。它最突出的贡献可能是围绕“行为”监督及其立法者的解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithms patrolling content: where’s the harm?
At the heart of this paper is an examination of the colloquial concept of a ‘shadow ban’. It reveals ways in which algorithms on the Facebook platform have the effect of suppressing content distribution without specifically targeting it for removal, and examines the consequential stifling of users’ speech. It reveals how the Facebook shadow ban is implemented by blocking dissemination of content in News Feed. The decision-making criteria are based on ‘behaviour’, a term that relates to activity of the page that is identifiable through patterns in the data. It’s a technique that is rooted in computer security, and raises questions about the balance between security and freedom of expression. The paper is situated in the field of responsibility of online platforms for content moderation. It studies the experience of the shadow ban on 20 UK-based Facebook Pages over the period from November 2019 to January 2021. The potential harm was evaluated using human rights standards and a comparative metric produced from Facebook Insights data. The empirical research is connected to recent legislative developments: the EU’s Digital Services Act and the UK’s Online Safety Bill. Its most salient contribution may be around ‘behaviour’ monitoring and its interpretation by legislators.
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来源期刊
CiteScore
3.70
自引率
0.00%
发文量
25
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