A Visualization Approach for Understanding the Dynamics of Academic Careers
INTRODUCTION
AUTHORS
MATERIALS
How to achieve individual career success is a long-standing research question that has been studied in various social science disciplines, such as sociology, organizational behaviors, and information science. With the increased availability of academic profiles such as researchers’ careers and scientific outputs, academic careers have become one of the prominent topics in the study of careers that attracts the attention of both social scientists and general researchers. Social scientists want to unravel factors that will positively or negatively contribute to academic career success. Researchers in other disciplines are concerned with how to raise scientific productivity and achieve career success. This line of research has regained its prominence with the emergence of Science of Science in the age of computational social science.
In this study, we adopt an innovative dynamic perspective to examine how individual and social factors will influence career success over time. We propose ACSeeker, an interactive visual analytics approach to explore the potential factors of success and how the influence of multiple factors changes at different stages of academic careers.
We first applied a Multi-factor Impact Analysis framework to estimate the effect of different factors on academic career success over time. The whole framework consists of four components: sequence slicing, sequence clustering, multivariate linear regression, and cluster alignment.
We then developed a visual analytics system to understand the dynamic effects interactively. A novel timeline is designed to reveal and compare the factor impacts based on the whole population. A customized career line showing the individual career development is provided to allow a detailed inspection.
1
2
To validate the effectiveness and usability of ACSeeker, we report two case studies and interviews with a social scientist and general researchers.
3
4
Demo Video.
Yifang WANG
Taiquan PENG
Huihua LU
Haoren WANG
Xiao XIE
Huamin QU
Yingcai WU
ACSEEKER
Explore the Science of Science