Interactive Visual Analytics for Career Mobility

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering

PhD Thesis Defence

Title: "Interactive Visual Analytics for Career Mobility"


Miss Yifang WANG


Career mobility is a long-standing research topic in social science that 
investigates the trajectories of individuals in terms of their occupation 
transitions. It is crucial for the study of social stratification, 
inequality, and policy-making in multiple disciplines, such as sociology, 
economics, and political science. With the availability of longitudinal 
career-related datasets from quantitative history and sociology, 
traditional statistical approaches are facing three challenges in 
analyzing these complex data given their sequential, network, and 
multivariate natures: (1) the lack of analysis from a dynamic longitudinal 
perspective, (2) the insufficient analysis of potential factors (such as 
social relations) that may affect careers, and (3) the lack of efficient 
tools to support exploring career mobility from different dimensions 
flexibly. In the meantime, visual analytics allows feeding domain 
knowledge into the interactive systems, which has brought new 
opportunities to solve the above three challenges efficiently. Social 
scientists can thus verify existing theories and generate new hypotheses 
under a human-computer collaboration process conveniently.

In this thesis, we focus on designing visual analytics systems for social 
scientists to address career mobility analytical problems efficiently from 
three perspectives. In the first work, we aim to obtain career mobility 
patterns to understand social mobility in different periods. We present 
CareerLens to explore over 340,000 government officials’ careers in the 
Qing bureaucracy in China. After obtaining career mobility patterns, a 
further step is to learn how potential factors that may affect one’s 
career. In the second work, we expand the scope of our research to 
academic careers and develop ACSeeker to investigate potential individual 
(e.g., working domain) and social factors (e.g., social relations) that 
may affect career mobility. Besides career-related factors, another 
important perspective that may significantly affect careers is private 
lives, such as marriage and childbearing. In addition, they may have a 
cumulative effect on careers. In the third work, we use WLViz to explore 
and compare work-family dynamics of different social groups (e.g., male 
and female groups). Finally, we discuss the future research perspectives 
on building visual analytics systems to facilitate career mobility and 
social science studies.

Date:			Friday, 29 July 2022

Time:			2:00pm - 4:00pm

Zoom Meeting:

Chairperson:		Prof. James LEE (SOSC)

Committee Members:	Prof. Huamin QU (Supervisor)
 			Prof. Xiaojuan MA
 			Prof. Dan XU
 			Prof. Han ZHANG (SOSC)
 			Prof. Jun WANG (Peking University)

**** ALL are Welcome ****