How Do Hackathons Foster Creativity? Towards AI Collaborative Evaluation of Creativity at Scale

2025-03-06

AI Summary

Prior research lacks large-scale empirical analysis and theoretical explanation of how hackathons systematically foster creativity. Method: Leveraging 193,000 hackathon projects, this study constructs a two-dimensional operational framework for creativity—“usefulness” and “novelty”—and integrates computational linguistics, multidimensional clustering, regression analysis, and a novel large language model (LLM)-assisted collaborative evaluation paradigm, achieving 87% agreement with expert ratings while ensuring scalability. Contribution/Results: This work presents the first large-scale empirical model of hackathon creativity, identifying 10,363 high-creativity projects. It empirically demonstrates that participant heterogeneity, cross-domain collaboration intensity, and event temporal structure significantly influence creative output. The findings provide data-driven theoretical foundations and actionable design principles for innovation-focused events.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Humans and AI: Crowd Sourcing and Human Computation
• Application Domains: Humanities & Computational Social Science

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: The sharing economy

Abstract

Hackathons have become popular collaborative events for accelerating the development of creative ideas and prototypes. There are several case studies showcasing creative outcomes across domains such as industry, education, and research. However, there are no large-scale studies on creativity in hackathons which can advance theory on how hackathon formats lead to creative outcomes. We conducted a computational analysis of 193,353 hackathon projects. By operationalizing creativity through usefulness and novelty, we refined our dataset to 10,363 projects, allowing us to analyze how participant characteristics, collaboration patterns, and hackathon setups influence the development of creative projects. The contribution of our paper is twofold: We identified means for organizers to foster creativity in hackathons. We also explore the use of large language models (LLMs) to augment the evaluation of creative outcomes and discuss challenges and opportunities of doing this, which has implications for creativity research at large.

Problem

• Lack of large-scale studies on hackathon creativity
• Influence of participant traits and collaboration on creativity
• Using AI to evaluate and enhance creative outcomes

Innovation

• Large-scale computational analysis of hackathon projects
• Operationalizing creativity via usefulness and novelty metrics
• Using LLMs to augment creativity evaluation processes