A Survey on Computational Approaches to Understanding and Facilitating Support in Online Health Communities

PhD Qualifying Examination


Title: "A Survey on Computational Approaches to Understanding and 
Facilitating Support in Online Health Communities"

by

Mr. Qingyu GUO


Abstract:

People join online health communities (OHCs) to seek and provide social 
support around health-related issues, such as cancer, depression, and 
medical bills. However, challenges exist in attracting and providing 
high-quality support. In recent years, computational approaches to 
understanding and improving the support efficacy (i.e., communication 
ten-dency, community wellness, and individual wellness) in OHCs have 
attracted great attention due to their practicality and scalability. In 
this survey, we review the state-of-the-art research in this domain and 
categorize them into three groups: factor identification, factor and 
support efficacy modeling, and support enhancement methods. We first 
introduce factors associated with three aspects of support efficacy, 
followed by a summary of the analyzing techniques and research 
opportunities. Then we present major modeling tasks that could potentially 
facilitate members in OHCs, including seeker content under-standing, 
provider content evaluation, and support efficacy prediction. Next, we 
illustrate existing computational techniques to enhance support in OHCs, 
divided into rule-based and generation-based methods. Finally, we discuss 
several potential research directions and challenges in this field.


Date:			Thursday, 28 April 2022

Time:                  	10:00am - 12:00noon

Zoom Meeting: 
https://hkust.zoom.us/j/91074976335?pwd=REZ6dFJnUk1PTmVmcE9ZYTcrdWJtUT09

Committee Members:	Dr. Xiaojuan Ma (Supervisor)
 			Dr. Yangqiu Song (Chairperson)
 			Prof. Qiong Luo
 			Dr. Hao Liu (AI Thrust)


**** ALL are Welcome ****