Let's Influence Algorithms Together: How Millions of Fans Build Collective Understanding of Algorithms and Organize Coordinated Algorithmic Actions

Qing Xiao, Yuhang Zheng, Xianzhe Fan, Bingbing Zhang, Zhicong Lu
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Abstract

Previous research pays attention to how users strategically understand and consciously interact with algorithms but mainly focuses on an individual level, making it difficult to explore how users within communities could develop a collective understanding of algorithms and organize collective algorithmic actions. Through a two-year ethnography of online fan activities, this study investigates 43 core fans who always organize large-scale fans' collective actions and their corresponding general fan groups. This study aims to reveal how these core fans mobilize millions of general fans through collective algorithmic actions. These core fans reported the rhetorical strategies used to persuade general fans, the steps taken to build a collective understanding of algorithms, and the collaborative processes that adapt collective actions across platforms and cultures. Our findings highlight the key factors that enable computer-supported collective algorithmic actions and extend collective action research into large-scale domain targeting algorithms.
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让我们一起影响算法:数百万粉丝如何建立对算法的集体理解并组织协调算法行动
以往的研究关注用户如何战略性地理解算法并有意识地与算法互动,但主要集中在个人层面,难以探索社区内的用户如何形成对算法的集体理解并组织集体算法互动。本研究通过对网络粉丝活动进行为期两年的人种学研究,调查了 43 名经常组织大规模粉丝集体活动的核心粉丝及其相应的普通粉丝群体。本研究旨在揭示这些核心粉丝如何通过集体算法行动动员数百万普通粉丝。这些核心粉丝报告了用于说服普通粉丝的修辞策略、建立对算法的集体理解所采取的步骤,以及调整跨平台和跨文化集体行动的协作过程。我们的研究结果强调了计算机支持集体算法行动的关键因素,并将集体行动研究扩展到了大规模领域目标算法。
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