Modeling and Analysis of Scholar Mobility on Scientific Landscape

TL;DR

This paper introduces an agent-based model to analyze how scholars choose research topics and migrate across the scientific landscape, providing insights into the effects of different strategies on individual success and societal diversity.

Contribution

It presents a novel agent-based modeling framework for studying scholar mobility and its impact on scientific progress and diversity.

Findings

Different strategies influence success and diversity in research

Choosing topics based on potential or popularity affects scientific landscape

Model offers a way to analyze and optimize scholarly behavior

Abstract

Scientific literature till date can be thought of as a partially revealed landscape, where scholars continue to unveil hidden knowledge by exploring novel research topics. How do scholars explore the scientific landscape , i.e., choose research topics to work on? We propose an agent-based model of topic mobility behavior where scholars migrate across research topics on the space of science following different strategies, seeking different utilities. We use this model to study whether strategies widely used in current scientific community can provide a balance between individual scientific success and the efficiency and diversity of the whole academic society. Through extensive simulations, we provide insights into the roles of different strategies, such as choosing topics according to research potential or the popularity. Our model provides a conceptual framework and a computational approach to analyze scholars' behavior and its impact on scientific production. We also discuss how such an agent-based modeling approach can be integrated with big real-world scholarly data.