Decoding Success: Leveraging Crowdfunding Data to Predict Venture Outcomes and Assess Creative Complexity
Jermain Kaminski, School of Business and Economics, Maastricht University
Crowdfunding operates as an open and accessible laboratory for examining emerging creative ventures. In this presentation, the first segment explores the predictive power of text, speech, and video metadata analysis across more than 20,000 technology crowdfunding campaigns, utilizing machine learning tools to anticipate the potential success of startup pitches. Following this, economic complexity measures are employed to reveal the comparative advantages discerned in crowdfunding data, suggesting this approach as a new metric to gauge nascent creativity. While the two distinct analyses underscore the diverse opportunities presented by crowdfunding data, the limitations of machine learning for predictions are also discussed.
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About the speaker
Jermain Kaminski is an Assistant Professor at the School of Business and Economics at Maastricht University.
His teaching activities focus on technology entrepreneurship, innovation and applied data science. In his research, he combines techniques from data science, machine learning, and natural language processing.
Jermain studied at Witten/Herdecke University, Germany, and the Massachusetts Institute of Technology, USA. At MIT, he was a visiting researcher at the MIT Center for Collective Intelligence at the Sloan School of Management and the MIT Media Lab. Jermain completed his PhD studies (Dr. rer. pol.) at RWTH Aachen University. He is a co-founder of MovieGalaxies and co-chair of the Causal Data Science Meeting.
Venue: Room 0.18, Boschstraat 24, Maastricht (UNU-MERIT) and online (Zoom)
Date: 26 October 2023
Time: 11:00 - 12:00 CEST