时间：2025年12月5日10：00

Zoom会议号：861 4642 8149

Speaker: Shizhen Chen

Abstract:

Online communities frequently grapple with two fundamental challenges in collective action projects: coordinating strategy and mobilizing broad-based participation. This study posits that the structure of influence within an online community significantly impacts its efficacy in addressing these challenges. Specifically, we argue that communities with more hierarchical influence structures—where a concentrated few significantly shape others' behavior—excel at coordinating strategy but struggle with mobilizing participation. Conversely, flatter structures may face initial coordination hurdles but foster greater participation. We test these hypotheses using empirical data from Reddit's 2022 r/place event, where communities mobilize their members to construct artwork pixel-by-pixel on a shared digital canvas. Our findings reveal several key insights: Communities with more hierarchical influence structures demonstrate faster strategic decision-making, evidenced by earlier project initiation and more rapid initial progress toward their objectives. However, this early advantage shrinks as inter-community competition intensifies, increasing the imperative to mobilize marginal members. In these more demanding phases, flatter influence structures surpass their hierarchical counterparts in project progression rates. The performance improvement of flat communities is particularly pronounced when they possess a large contingent of marginal members who subscribe to community updates but do not actively participate in discussions. These findings advance our understanding of online community dynamics and offer crucial implications for the design and management of various online collective action projects, such as crowdfunding campaigns, online petitions, digital protests, and coordinated stock trades.

Introduction of Speaker：

Shizhen Chen is an Information Systems & Operations Management PhD student at Goizueta Business School. He will be on the 2025/2026 academic job market.

His research focuses on online communities, with particular interest in open collaboration, crowdsourcing, and collective action under high temporal dynamics. He applies computational and statistical methods (e.g., computer vision, survival modeling) to analyze unstructured trace data in r/place social experiment and uncover how dispersed individuals mobilize toward shared goals in digital environments.

Looking ahead, he envisions a future where advances in AI and digital technologies further expand the possibilities of online collective action. As tools for coordination, visualization, and intelligent assistance become increasingly accessible, large-scale collaborations (from to scientific computing projects like Folding@home to humanitarian mapping efforts such as OpenStreetMap) can generate even greater social and economic value. His ongoing work  aims to understand what drives some of these initiatives to thrive while others struggle, offering insights into how technology, motivation, and community structure jointly determine the success and sustainability of collective endeavors.