Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Crowdsourcing has become a porful paradigm for accomplishing work quickly and at scale, but involves significant challenges in quality control. Researchers have developed algorithmic quality control approaches based on either worker outputs (such as gold standards or worker agreement) or worker behavior (such as task fingerprinting), but each approach has serious limitations, especially for complex or creative work. Human evaluation addresses these limitations but does not scale ll with increasing numbers of workers.  present CrowdScape, a system that supports the human evaluation of complex crowd work through interactive visualization and mixed initiative machine learning. The system combines information about worker behavior with worker outputs, helping users to better understand and harness the crowd.  describe the system and discuss its utility through grounded case studies.  explore other contexts where CrowdScape's visualizations might be useful, such as in user studies.
['Jeffrey M. Rzeszotarski', 'Aniket Kittur']
I am writing a research paper on a idea CrowdScape: interactively visualizing user behavior and output
[{"from": "human", "value": "I am writing a research paper on a idea CrowdScape: interactively visualizing user behavior and output"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Crowdsourcing has become a porful paradigm for accomplishing work quickly and at scale, but involves significant challenges in quality control. Researchers have developed algorithmic quality control approaches based on either worker outputs (such as gold standards or worker agreement) or worker behavior (such as task fingerprinting), but each approach has serious limitations, especially for complex or creative work. Human evaluation addresses these limitations but does not scale ll with increasing numbers of workers.  present CrowdScape, a system that supports the human evaluation of complex crowd work through interactive visualization and mixed initiative machine learning. The system combines information about worker behavior with worker outputs, helping users to better understand and harness the crowd.  describe the system and discuss its utility through grounded case studies.  explore other contexts where CrowdScape's visualizations might be useful, such as in user studies."}]