Scalable Crowd Ideation Support through Data Visualization, Mining, and Structured Workflows

As the size of innovation communities increases, methods of supporting their creativity need to scale as well. Our research proposes the integration of three scalable techniques into a crowd ideation system: 1) data visualization, 2) structured microtask workflows, and 3) data mining, with the goal of supporting users in convergent and divergent ideation processes. In addition, these techniques do not work in isolation, but instead support each other. Our vision is to create a system that intelligently supports users' ideation in a crowd context while maintaining their agency and facilitating exploration and decision-making.