How Do Hackathons Foster Creativity? Towards AI Collaborative Evaluation of Creativity at Scale
This addresses a gap in understanding how hackathon formats foster creativity, with implications for organizers and creativity research, though it is incremental in applying computational methods to an existing problem.
The paper tackled the lack of large-scale studies on creativity in hackathons by analyzing 193,353 projects, refining to 10,363 based on usefulness and novelty, to identify factors like participant characteristics and collaboration patterns that influence creative outcomes, and explored using LLMs to augment evaluation.
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.