Interactive Visual Analytics for Career Mobility

PhD Thesis Proposal Defence


Title: "Interactive Visual Analytics for Career Mobility"

by

Miss Yifang WANG


Abstract:

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 proposal, 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. Finally, we discuss the 
ongoing work for visual analytics of work-family dynamics and future research 
perspectives on building visual analytics systems to facilitate career mobility 
and social science studies.


Date:			Thursday, 26 May 2022

Time:                  	2:00pm - 4:00pm

Zoom Meeting:
https://hkust.zoom.us/j/93082128285?pwd=bHBaZml6VUxOU1A2VGRQaGdRZXFHZz09

Committee Members:	Prof. Huamin Qu (Supervisor)
  			Prof. Pedro Sander (Chairperson)
 			Prof. Raymond Wong
 			Prof. Cameron Campbell (SOSC)


**** ALL are Welcome ****