当桥梁不是人类时算法通过操纵弱关系干扰社会关系的形成

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Patricia A. Norberg, Daniel R. Horne
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引用次数: 0

摘要

近年来,社交媒体应用程序的数量和用户群都在不断增长。这些平台上的推荐算法将社交他人和相关内容推荐给用户。利用格兰诺维特的纽带强度理论和有关关系形成的文献作为概念基础,我们认为,这些社交媒体算法会损害用户建立各种关系的能力和从中获益的能力,从而降低个人优势,并在汇总后降低社会优势。我们认为,之所以会出现这种情况,是因为这些算法扮演了社会行动者的角色,并作为 "弱纽带冒名顶替者 "运作,成为连接喜欢的人和内容的桥梁。这项研究为推荐算法在社会关系中扮演的角色提供了一个新的概念,论证了推荐算法如何影响社会关系的发展和用户隐私,并为算法干扰相关问题提供了潜在的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
When the bridge is not human: Algorithmic interference in forming social relationships through the manipulation of weak ties

In recent years, social media applications have grown in number and in user bases. Recommendation algorithms on these platforms refer social others and related content to users. Using Granovetter's tie strength theory and the literature on relationship formation as conceptual foundations, we argue that these social media algorithms can damage a user's ability to establish diverse relationships and the benefits therein, thereby reducing personal, and, when aggregated, societal advantages. We argue that this occurs because the algorithms take on social actor roles and operate as “weak tie imposters” that serve as bridges to like others and content. This work provides a new conceptualization of the role recommendation algorithms play in social relationships, argues how they impact social relationship development and user privacy, and offers potential solutions to the issues related to algorithmic interference.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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