Supporting informal communication via ephemeral interest groups
CSCW '92 Proceedings of the 1992 ACM conference on Computer-supported cooperative work
The dynamics of mass interaction
CSCW '98 Proceedings of the 1998 ACM conference on Computer supported cooperative work
The Wisdom of Crowds
Working for Free? Motivations for Participating in Open-Source Projects
International Journal of Electronic Commerce
Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business
Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business
Designing crowdsourcing community for the enterprise
Proceedings of the ACM SIGKDD Workshop on Human Computation
Towards a research agenda for enterprise crowdsourcing
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part I
Perceived and Actual Role of Gamification Principles
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
Hi-index | 0.00 |
In large scale online multi-user communities, the phenomenon of 'participation inequality,' has been described as generally following a more or less 90-9-1 rule [9]. In this paper, we examine crowdsourcing participation levels inside the enterprise (within a company's firewall) and show that it is possible to achieve a more equitable distribution of 33-66-1. Accordingly, we propose a SCOUT ((S)uper Contributor, (C)ontributor, and (OUT)lier)) model for describing user participation based on quantifiable effort-level metrics. In support of this framework, we present an analysis that measures the quantity of contributions correlated with responses to motivation and incentives. In conclusion, SCOUT provides the task-based categories to characterize participation inequality that is evident in online communities, and crucially, also demonstrates the inequality curve (and associated characteristics) in the enterprise domain.