Relation
Crowdsourcing Workflows: Collaborative Planning and Execution
- The results of the previous section suggest that the crowd can sometimes produce acceptable results in planning and executing solutions to general requests, but more frequently face challenges.
- This section elaborates more on informal experiments for both approaches, first with an expert crowd of workers recruited at UC Berkeley, and the second with a Mechanical Turk crowd.
- Researchers re-ran the essay-writing, blog creation, and natural-language query tasks discussed earlier.
At least two different strategies to address these challenges are plausible:
- The first strategy is to recruit more expert workers.
- The second strategy is to allow requesters to monitor and selectively intervene in the process.
Additional Sections:
- Outcome
- Discussion: Why Does Collaborative Workflow Creation Succeed?
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Updated 2021-07-05
Tags
Psychology
Social Science
Empirical Science
Science
Related
Collaboratively crowdsourcing workflows with Turkomatic
Crowdsourcing Workflows: Introduction
Crowdsourcing Workflows: Related Work
Crowdsourcing Workflows: The Turkomatic System
Crowdsourcing Workflows: How Well Can Crowds Plan and Execute?
Crowdsourcing Workflows: Collaborative Planning and Execution
Crowdsourcing Workflows: User Experiences with Turkomatic
Crowdsourcing Workflows: Discussion
Crowdsourcing Workflows: Conclusion