Scientists' bounded mobility on the epistemic landscape
Shuang Zhang, Feifan Liu, Haoxiang Xia

TL;DR
This study analyzes scientists' movement within the knowledge space, revealing bounded exploration patterns, their impact on academic performance, and proposing a model to simulate these behaviors, with implications for science policy.
Contribution
Introduces a bounded exploration-exploitation model based on large-scale bibliometric data to explain scientists' research mobility patterns and their effects on academic impact.
Findings
Scientists' transition radii and paces are left-skewed.
Scientists exhibit mixed exploration and exploitation behaviors.
Extensive exploration correlates with decreased impact.
Abstract
Despite persistent efforts in revealing the temporal patterns in scientific careers, little attention has been paid to the spatial patterns of scientific activities in the knowledge space. Here, drawing on millions of papers in six disciplines, we consider scientists' publication sequence as "walks" on the quantifiable epistemic landscape constructed from large-scale bibliometric corpora by combining embedding and manifold learning algorithms, aiming to reveal the individual research topic dynamics and association between research radius with academic performance, along their careers. Intuitively, the visualization shows the localized and bounded nature of mobile trajectories. We further find that the distributions of scientists' transition radius and transition pace are both left-skewed compared with the results of controlled experiments. Then, we observe the mixed exploration and…
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Taxonomy
TopicsComplex Network Analysis Techniques · scientometrics and bibliometrics research · Complex Systems and Time Series Analysis
