Inspiration or Preparation? Explaining Creativity in Scientific Enterprise

TL;DR

This study investigates the mechanisms of scientific creativity by analyzing authors' information consumption versus their knowledge outputs, revealing that a significant portion of creativity can be explained by consumed information and enabling predictive identification of critical knowledge for innovation.

Contribution

It introduces a fine-grained analysis of scientific creative processes using large-scale data and develops a predictive framework for identifying knowledge critical to scientific innovation.

Findings

25.7% of papers' creativity explained by authors' information consumption

Developed a framework to predict critical knowledge for innovation

Insights for designing better information recommendation systems

Abstract

Human creativity is the ultimate driving force behind scientific progress. While the building blocks of innovations are often embodied in existing knowledge, it is creativity that blends seemingly disparate ideas. Existing studies have made striding advances in quantifying creativity of scientific publications by investigating their citation relationships. Yet, little is known hitherto about the underlying mechanisms governing scientific creative processes, largely due to that a paper's references, at best, only partially reflect its authors' actual information consumption. This work represents an initial step towards fine-grained understanding of creative processes in scientific enterprise. In specific, using two web-scale longitudinal datasets (120.1 million papers and 53.5 billion web requests spanning 4 years), we directly contrast authors' information consumption behaviors against their knowledge products. We find that, of 59.0\% papers across all scientific fields, 25.7\% of their creativity can be readily explained by information consumed by their authors. Further, by leveraging these findings, we develop a predictive framework that accurately identifies the most critical knowledge to fostering target scientific innovations. We believe that our framework is of fundamental importance to the study of scientific creativity. It promotes strategies to stimulate and potentially automate creative processes, and provides insights towards more effective designs of information recommendation platforms.