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
摘要
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.
• Human-centered computing → Empirical studies in HCI .
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper7
- Do Teachers Dream of GenAI Widening Educational (In)equality? Envisioning the Future of K-12 GenAI Education from Global Teachers' PerspectivesRuiwei Xiao, Qing Xiao, Xinying Hou, Phenyo Phemelo Moletsane 等CHI 2026 · 被引用 4 次
- Robots that Evolve with Us: Modular Co-Design for Personalization, Adaptability, and SustainabilityLingyun Chen, Qing Xiao, Zitao Zhang, Eli Blevis 等CHI 2026 · 被引用 2 次
- Power Echoes: Investigating Moderation Biases in Online Power-Asymmetric ConflictsYaqiong Li, Peng Zhang, Peixu Hou, Kainan Tu 等CHI 2026 · 被引用 2 次
- Can GenAI Move from Individual Use to Collaborative Work? Experiences, Challenges, and Opportunities of Coordinating GenAI into Collaborative NewsworkQing Xiao, Qing Hu, Jingjia Xiao, Hancheng Cao 等CHI 2026 · 被引用 1 次
- People Can Accurately Predict Behavior of Complex Algorithms That Are Available, Compact, and Aligned CSCW031Lindsay Popowski, Helena Vasconcelos, Ignacio Javier Fernandez, Chijioke Chinaza Mgbahurike 等CSCW 2026
它引用的顶会 Paper11
- Algorithmic Folk Theories and Identity: How TikTok Users Co-Produce Knowledge of Identity and Engage in Algorithmic ResistanceNadia Karizat, Daniel Delmonaco, Motahhare Eslami, Nazanin AndalibiCSCW 2021 · 被引用 338 次
- Everyday Algorithm Auditing: Understanding the Power of Everyday Users in Surfacing Harmful Algorithmic BehaviorsHong Shen, Alicia DeVos, Motahhare Eslami, Kenneth HolsteinCSCW 2021 · 被引用 156 次
- Adaptive Folk Theorization as a Path to Algorithmic Literacy on Changing PlatformsMichael Ann DeVitoCSCW 2021 · 被引用 143 次
- How Transfeminine TikTok Creators Navigate the Algorithmic Trap of Visibility Via Folk TheorizationMichael Ann DeVitoCSCW 2022 · 被引用 125 次
- Toward User-Driven Algorithm Auditing: Investigating users' strategies for uncovering harmful algorithmic behaviorAlicia DeVos, Aditi Dhabalia, Hong Shen, Kenneth Holstein 等CHI 2022 · 被引用 96 次
相关 Paper
- "To be that one other brick in the pillar": Online Communities, Platforms, and Collective Action in the BTS Industrial ComplexKathryn E. Ringland, Bhavani Seetharaman, Jhertau Her, Angeleen Tan 等CHI 2026 · 被引用 1 次
- Armed in ARMY: A Case Study of How BTS Fans Successfully Collaborated to #MatchAMillion for Black Lives MatterSo Yeon Park, Nicole K. Santero, Blair Kaneshiro, Jin Ha LeeCHI 2021 · 被引用 62 次
- ARMY's Magic Shop: Understanding the Collaborative Construction of Playful Places in Online CommunitiesKathryn E. Ringland, Arpita Bhattacharya, Kevin Weatherwax, Tessa Eagle 等CHI 2022 · 被引用 25 次
- The Algorithm and the Org Chart: How Algorithms Can Conflict with Organizational StructuresMelissa A. Valentine, Amanda L. Pratt, Rebecca Hinds, Michael S. BernsteinCSCW 2024 · 被引用 4 次
- Participation and Division of Labor in User-Driven Algorithm Audits: How Do Everyday Users Work together to Surface Algorithmic Harms?Rena Li, Sara Kingsley, Chelsea Fan, Proteeti Sinha 等CHI 2023 · 被引用 28 次
