Abstract

The selection of research topics by scientists can be viewed as an exploration process conducted by individuals with cognitive limitations traversing a complex cognitive landscape influenced by both individual and social factors. While existing theoretical investigations have provided valuable insights, the intricate and multifaceted nature of modern science hinders the implementation of empirical experiments. This study leverages advancements in Geographic Information System (GIS) techniques to investigate the patterns and dynamic mechanisms of topic-transition among scientists. By constructing the knowledge space across 6 large-scale disciplines, we depict the trajectories of scientists’ topic transitions within this space, measuring the flow and distance of research regions across different sub-spaces. Our findings reveal a predominantly conservative pattern of topic transition at the individual level, with scientists primarily exploring local knowledge spaces. Furthermore, simulation modeling analysis identifies research intensity, driven by the concentration of scientists within a specific region, as the key facilitator of topic transition. Conversely, the knowledge distance between fields serves as a significant barrier to exploration. Notably, despite potential opportunities for breakthrough discoveries at the intersection of subfields, empirical evidence suggests that these opportunities do not exert a strong pull on scientists, leading them to favor familiar research areas. Our study provides valuable insights into the exploration dynamics of scientific knowledge production, highlighting the influence of individual cognition, social factors, and the intrinsic structure of the knowledge landscape itself. These findings offer a framework for understanding and potentially shaping the course of scientific progress.

中文翻译：

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科学作为知识领域的探索：追踪热点还是寻找机会？

摘要

科学家对研究主题的选择可以被视为具有认知局限性的个体在受个人和社会因素影响的复杂认知景观中进行的探索过程。虽然现有的理论研究提供了有价值的见解，但现代科学的复杂性和多面性阻碍了实证实验的实施。本研究利用地理信息系统（GIS）技术的进步来研究科学家之间主题转换的模式和动态机制。通过构建跨6个大规模学科的知识空间，我们描绘了该空间内科学家的主题转换轨迹，测量了不同子空间中研究区域的流动和距离。我们的研究结果揭示了个人层面上主题转换的保守模式，科学家主要探索本地知识空间。此外，仿真建模分析将由特定区域内科学家集中所驱动的研究强度确定为主题转换的关键促进因素。相反，领域之间的知识距离成为探索的重大障碍。值得注意的是，尽管在子领域的交叉点上存在突破性发现的潜在机会，但经验证据表明，这些机会并没有对科学家产生强大的吸引力，导致他们倾向于熟悉的研究领域。我们的研究为科学知识生产的探索动态提供了宝贵的见解，强调了个人认知、社会因素和知识景观本身内在结构的影响。这些发现为理解和潜在地塑造科学进步的进程提供了一个框架。