| NSF Org: |
IIS Div Of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | July 5, 2016 |
| Latest Amendment Date: | September 5, 2017 |
| Award Number: | 1617129 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
William Bainbridge
IIS Div Of Information & Intelligent Systems CSE Direct For Computer & Info Scie & Enginr |
| Start Date: | September 1, 2016 |
| End Date: | August 31, 2021 (Estimated) |
| Total Intended Award Amount: | $305,359.00 |
| Total Awarded Amount to Date: | $305,359.00 |
| Funds Obligated to Date: |
FY 2017 = $191,056.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
4333 BROOKLYN AVE NE SEATTLE WA US 98195-1016 (206)543-4043 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
4333 Brooklyn Avenue, Box 359472 Seattle WA US 98195-0001 |
| Primary Place of Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | HCC-Human-Centered Computing |
| Primary Program Source: |
01001718DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Together with the team at Northwestern University, the Pathways to Community Success project led by PI Hill and his team at the University of Washington made important empirical, theoretical, methodological, and practical contributions to organization-level research online communities. Work on the grant sparked the creation of a joint research group called the Community Data Science Collective which has, over the period of the award, become a premier research group working on computational studies of online communities.
The work contributed to knowledge at the intersection of social computing and human collaboration by using organizational theory to draw inference about factors that shape the growth and effectiveness of peer production systems. In particular, the research team produced a series of empirical projects testing major theories of peer production growth using data from a large population of peer production wikis as well as several other data sources. Results from these studies advanced scientific understanding of collaborative organization by testing several of the most important theories of peer production and evaluating these theories through large-scale longitudinal comparison of many peer production systems.
The award has resulted in nine peer reviewed papers, two peer reviewed poster presentations and short papers, two book chapters, four datasets, one piece of research software, and more than a dozen other talks and conference presentations. The work has also resulted in multiple awards and supported two masters theses and two PhD dissertations.
The broader impacts of the award are two-fold: First, it has contributed to actionable insights and novel theoretical approaches that communities, system designers, organizations, and movements engaged in online collaboration can use to achieve their collaborative goals at different stages of their projects. For example, members of the team shared their work with researchers and managers at companies and non-profit organizations running large online communities.
Additionally, the work generated a set of freely licensed and publicly available computational research systems and datasets which other researchers have used in their projects. In both ways, the work has contributed to the design of more effective and more collaborative organizations in online communities, in business, and in society.
Last Modified: 04/26/2022
Modified by: Benjamin Mako Hill
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