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

2024-09-16

arXiv.org

AI Summary

This study addresses the challenge of organizing effective user interventions against algorithmic opacity, focusing on how fan communities collaboratively construct algorithmic literacy and initiate cross-platform collective algorithmic action. Drawing on a two-year digital ethnography, it traces 43 core fans and their extended network of millions of ordinary fans, employing in-depth interviews, participant observation, cross-platform action tracking, and discourse analysis. The research makes three key contributions: first, it demonstrates—empirically—that algorithmic cognition can emerge through community-based collaboration; second, it introduces “collective algorithmic action” as a novel theoretical paradigm, extending collective action theory to large-scale algorithmic intervention contexts; third, it identifies mobilization strategies, consensus-building pathways, and cross-cultural coordination mechanisms, distilling six critical enablers for scalable, sustained collective algorithmic action.

Technology Category

• Humans and AI: Crowd Sourcing and Human Computation
• Application Domains: Humanities & Computational Social Science
• Search and Optimization: Algorithm Configuration

Application Category

• Responsible Web: Algorithmic accountability and transparency on the web
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

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 the large-scale domain targeting algorithms.

Problem

• Collective understanding of algorithms
• Organizing coordinated algorithmic actions
• Mobilizing large-scale fan communities

Innovation

• Collective algorithmic actions
• Community-driven understanding
• Cross-platform collaboration strategies