Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
A robust and scalable clustering algorithm for mixed type attributes in large database environment
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Cyperspace: The World in the Wires
Cyperspace: The World in the Wires
Collective Intelligence: Mankind's Emerging World in Cyberspace
Collective Intelligence: Mankind's Emerging World in Cyberspace
Organizing and the Process of Sensemaking
Organization Science
The Economic Leverage of the Virtual Community
International Journal of Electronic Commerce
An approach to quantitatively measuring collaborative performance in online conversations
Computers in Human Behavior
Open Social Networking for Online Collaboration
International Journal of e-Collaboration
Open Social Networking for Online Collaboration
International Journal of e-Collaboration
| Hi-index | 0.00 |
By monitoring online conversations, organizations can receive value from the intellectual activity of their most interested constituents as they engage in problem solving and ideation. However, since intergroup dynamics often hinders people from optimizing collaboration, it should be measured and monitored for quality. Current metrics assess collaborative value solely from the number of collaborators, assuming that differences between individuals can be ignored. This study found that assumption to be wrong by identifying three distinct collaborator segments that strongly differ in the timing of their participation and in the variety of ideas they introduce. Therefore, a new metric is proposed that takes into account the diverse value individuals add. This new measure is correlated with existing measures only in those infrequent situations when collaboration productivity is maximized.