KickstarterDataAnalysis

NameKickstarterDataAnalysis
DescriptionProject Description: Over the past five years, there has been a boom in technology startups that continues to attract more and more talent. While everyone starts with a million-dollar idea, only a few manage to transfer into real innovations and impact our lives. What makes those ideas successful? Can you imagine an app that tells you how innovative your idea is? This project will take a computational approach to the understanding of innovation and develop a machinery to learn from real data to evaluate the creativity of new ideas. Innovation is a broad topic, constantly discussed in business, economics, sociology, etc. It is such a complex phenomenon that there is no thorough theory about it. Here we will take a combinatorial perspective: an idea is a combination of existing and new knowledge. Hence, the goal is to understand why certain combinations are more interesting than others. Specifically, the first step is to map out our idea space with data from kickstarter, US Patents, and possibly other knowledge databases. The second step is to find interesting patterns, associations and dynamics in this map of knowledge. And finally computational methods will be developed to evaluate the fitness of any idea in a given environment.
OrganizationUniversity of Chicago
DepartmentComputation Institute
Sponsor Campus GridOSG Connect
Principal Investigator
Feng Bill Shi
Field Of ScienceStatistics
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