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Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Accelerating the review of complex intellectual artifacts in crowdsourced innovation challenges |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Event Title | Thirty Seventh International Conference on Information Systems |
| Event Type | conference |
| Event Location | Dublin 2016 |
| Event Start Date | December 11 - 2016 |
| Event End Date | December 14 - 2016 |
| Place of Publication | Dublin |
| Abstract Text | A critical bottleneck in crowdsourced innovation challenges is the process of reviewing and selecting the best submissions. This bottleneck is especially problematic in settings where submissions are complex intellectual artifacts whose evaluation requires expertise. To help reduce the review load from experts, we offer a computational approach that relies on analyzing sociolinguistic and other characteristics of submission text, as well as activities of the crowd and the submission authors, and scores the submissions. We developed and tested models based on data from contests done in a large citizen-science platform - the Climate CoLab - and find that they are able to accurately predict expert decisions about the submissions, and can lead to substantial reduction of review labor, and acceleration of the review process. |
| Official URL | http://icis2016.aisnet.org/ |
| Other Identification Number | merlin-id:13916 |
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