Detecting intellectual structure of a knowledge domain is valuable to track the dynamics of scientific research. Formal concept analysis (FCA) provides a new perspective for knowledge discovery and data mining. In this paper we introduce a FCA-based approach to detect intellectual structure of library and information science (LIS). Our approach relies on the mathematical theory which formulates the understanding of ''concept'' as a unit of extension (scholars) and intension (keywords) as a way of modelling the intellectual structure of a domain. By analyzing the papers published in sixteen prominent journals of LIS domain from 2001 to 2013, the intellectual structure of LIS in the new century has been identified and visualized. Nine major research themes of LIS were detected together with the core keywords and authors to describe each theme. The significant advantage of our approach is that the mathematical formulae produce a conceptual structure which automatically provides generalization and specialization relationships among the concepts. This provides additional information not available from other methods, especially when shared interests of authors from different granularities are also visualized in concept lattice.Keywords Formal concept analysis Á Intellectual structure Á Library and information science Electronic supplementary material The online version of this article (
We examine the influence of the COVID‐19 pandemic on medical occupation preference, focusing on Wuhan, China. We conducted a survey of 5686 respondents in China regarding the influence of the COVID‐19 pandemic on medical occupation preference. We also conducted a complimentary survey in the UK with 1198 respondents, as well as a field experiment in Wuhan with 428 first and second‐year medical students. We find a significant negative impact of the pandemic on the willingness to let a loved one choose a medical occupation. Individuals who were heavily influenced by the pandemic, that is, Wuhan residents, especially medical workers, express significantly lower medical occupation preference. Further analysis from Sobel‐Goodman mediation tests reveals that around half of the total negative effect can be mediated by enhanced risk aversion and reduced altruism. The UK survey and the field experiment with medical students in Wuhan reinforce these findings. Our results suggest a shift in medical workers' risk‐ and altruistic‐preferences has led to a reduced medical occupation preference. Non‐medical workers and students who are more altruistic and risk‐seeking are more likely to choose a medical occupation.
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