CHS: Small: Collaborative Research: Pathways to Community Success: Advancing a Comparative Science of Online Collaborative Organization

CHS：小型：协作研究：社区成功之路：推进在线协作组织的比较科学

• 批准号: 1617129
• 负责人: Benjamin Mako Hill
• 金额: $ 30.54万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1617129&HistoricalAwards=false
• 关键词: CHS; Small; Collaborative; Research; Pathways

This research project seeks to understand the factors that encourage success in computer-supported peer production - the form of online collaborative organization used to create public information goods like Wikipedia and Linux. Why do some peer production systems mobilize large communities of contributors and create valuable information goods while most do not? One answer for this challenging question is that success-related factors may change significantly as a collaborative organization grows, such that conditions that encouraged explosive growth in the beginning may prevent further growth later on. This work will provide actionable insights for initiators and managers of online collaborative organizations, informing the design and management of distributed collaboration across different topic domains at different stages of project development. It will also produce freely licensed and publicly available computational research systems and datasets that will enable reproducible research and the dissemination of the new techniques developed by the research. Peer production and related forms of online collaboration in virtual communities have diffused widely in software production, knowledge management, cultural production, and education. Another sign of its significance is the fact that a growing number of organizations look to distributed collaboration managed through virtual and volunteer communities as a source of innovation and customer support.This research uses longitudinal comparative analysis of populations of peer production communities to elaborate a novel and transformative science of pathways to effective collaborative organization. In doing so, it will extend the rich traditions of sociotechnical systems research and organization science on these topics. This empirical work will explore three central facets of peer production: (1) the relationship between participation equality and growth; (2) the extent to which community effectiveness is limited by competition for volunteer resources; and (3) the role of social interaction and coordination in productive collaboration. In every case, empirical predictions will be developed from prior work and tested using trace data from a large population of peer production wikis. The research will then explore how the observed relationships may diminish or even reverse as communities grow. The findings will become the basis for a broader theory of collaborative organization that explains how key drivers of mobilization in nascent groups differ systematically from those in established communities.

本研究项目旨在了解鼓励成功的因素，在计算机支持的同行生产-在线协作组织的形式，用于创建公共信息产品，如维基百科和Linux。 为什么有些同行生产系统动员了大量的贡献者社区，创造了有价值的信息产品，而大多数人却没有？ 这个具有挑战性的问题的一个答案是，随着协作组织的发展，与成功相关的因素可能会发生显着变化，例如，在开始时鼓励爆炸性增长的条件可能会阻止以后的进一步增长。这项工作将为在线协作组织的发起人和管理者提供可操作的见解，在项目开发的不同阶段，为跨不同主题领域的分布式协作的设计和管理提供信息。它还将产生免费许可和公开提供的计算研究系统和数据集，这将使研究能够重复进行，并传播研究开发的新技术。 虚拟社区中的同行生产和相关形式的在线协作在软件生产、知识管理、文化生产和教育中广泛传播。它的重要性的另一个迹象是，越来越多的组织期待通过虚拟和志愿者社区管理的分布式协作作为创新和客户support.This研究的来源使用纵向比较分析人口的同行生产社区，阐述了一个新的和变革性的科学的途径，以有效的协作组织。在这样做的过程中，它将扩展社会技术系统研究和组织科学在这些主题上的丰富传统。 这项实证工作将探讨同伴生产的三个核心方面：（1）参与平等和增长之间的关系;（2）社区效率在多大程度上受到志愿者资源竞争的限制;（3）社会互动和协调在生产性合作中的作用。在每一种情况下，经验预测将从先前的工作中开发出来，并使用来自大量对等生产维基的跟踪数据进行测试。然后，研究将探讨观察到的关系如何随着社区的发展而减少甚至逆转。研究结果将成为一个更广泛的协作组织理论的基础，该理论解释了新生群体中动员的关键驱动因素与成熟社区中的动员因素如何系统地不同。

项目成果

The Wikipedia Adventure: Field Evaluation of an Interactive Tutorial for New Users

维基百科冒险：针对新用户的交互式教程的现场评估

• DOI: 10.1145/2998181.2998307
• 发表时间: 2017
• 期刊: Proceedings of the 20th ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW ’17
• 作者: Narayan, Sneha;Orlowitz, Jake;Morgan, Jonathan;Hill, Benjamin Mako;Shaw, Aaron
• 通讯作者: Shaw, Aaron

Who Uses Bots? A Statistical Analysis of Bot Usage in Moderation Teams

谁使用机器人？

• DOI: 10.1145/3334480.3382960
• 发表时间: 2020
• 期刊: CHI EA '20: Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
• 作者: Kiene, Charles;Hill, Benjamin Mako
• 通讯作者: Hill, Benjamin Mako