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Revisiting the exploration-exploitation behavior of scholars' research topic selection: Evidence from a large-scale bibliographic database

利用 偏爱 数据科学 选择(遗传算法) 计算机科学 比例(比率) 生产力 管理科学 人工智能 工程类 地理 地图学 计算机安全 宏观经济学 经济 微观经济学
作者
Shengzhi Huang,Wei Lu,Yi Bu,Yong Huang
出处
期刊:Information Processing and Management [Elsevier BV]
卷期号:59 (6): 103110-103110 被引量:32
标识
DOI:10.1016/j.ipm.2022.103110
摘要

• This paper proposes five novel research strategies under the exploration-exploitation behavior, and presents corresponding metrics to quantify and identify them. • The paper discloses the relationship between scientists’ research performance and their preference for research strategies, and analyzes the evolution pattern of the preference. • Results show that eminent scientists tend to follow academic frontiers, study diverse topics, explore emerging topics and innovative topic combinations, but exploit mature topics less often. We also figure out the potential reasons for the phenomenon. • Results show that successful scientists prefer to execute exploratory research strategies from the beginning of their career, and young scientists seem to be more creative. The research on studying exploration-exploitation behavior in topic choice has consistently been the focus of a great deal of attention. In this study, we propose five novel research strategies under exploration and exploitation based on the general but significant features of topics, and present a series of metrics to quantify and identify these strategies. We analyze the relationship between scientists’ research performance (i.e., productivity and impact) and their preference for different strategies, and examine the evolution of their preference in scientific careers through comprehensive statistical analysis. We employ a MAG dataset as our data source, and select about 30 million scientists from the computer science filed and their publications as our analysis objects. Our empirical analysis shows that productive and impactful scientists tend to follow academic frontiers, study diverse topics, explore emerging topics and combinatorial innovation, but exploit mature topics less often. We also figure out the potential reasons for the phenomenon. In addition, we find that successful scientists prefer to execute exploratory research strategies from the beginning of their career, and young scientists seem to be more creative. Our research may help researchers deeply understand topic selection behavior, and therefore provide enlightenment for training scientists and give advice for funding allocation as well as research and development policy formulation.
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