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.

翻译：黑客松已成为加速创意构思与原型开发的流行协作活动。现有多个案例研究展示了其在工业、教育和研究等领域的创造性成果。然而，目前缺乏关于黑客松创造力的大规模研究，这阻碍了关于黑客松组织形式如何催生创造性成果的理论发展。我们对193,353个黑客松项目进行了计算分析。通过将创造力操作化为实用性与新颖性两个维度，我们将数据集精炼至10,363个项目，以此分析参与者特征、协作模式及黑客松组织形式如何影响创意项目的开发。本文的贡献包括：为组织者提出了促进黑客松创造力的具体方法；探索了利用大语言模型（LLMs）增强创意成果评估的可行性，并讨论了该方法面临的挑战与机遇，这对广义的创造力研究具有重要启示。