DOI

10.17077/etd.e3veze0f

Document Type

Dissertation

Date of Degree

Spring 2017

Access Restrictions

Access restricted until 07/13/2019

Degree Name

PhD (Doctor of Philosophy)

Degree In

Informatics

First Advisor

Zhao, Kang

First Committee Member

Street, Nick

Second Committee Member

Pant, Gautam

Third Committee Member

Srinivasan, Padmini

Fourth Committee Member

Campo, Shelly

Abstract

Online Health Communities (OHCs) have become an important source of sharing and receiving information and support for people with health-related concerns. These communities provide important benefits to users including enhanced medical knowledge, emotional comfort, personal empowerment and the ability to create offline social connections. High levels of user engagement are beneficial to both users and the OHC, so it is important to understand what motivate users’ participation, encourage them to contribute and influence their churning behaviors.

This thesis covers why, when, and how users are actively engaged within an OHC. It is based on descriptive and predictive analytics of OHC users’ online interactions with text mining techniques. I built explanatory models to reveal how users’ motivations and roles evolve over time, the types of social support activities that encourage users’ continuous participation, and the forms of social capital that drive users’ continued contributions to the community. In addition, I developed predictive models to help an OHC forecast whether and when a user will churn.

The findings of this study have implications for managing and sustaining successful OHCs, and can provide OHC managers with suggestions on how to motivate user contributions and retain users through interventions.

Public Abstract

The ubiquity of the Internet access brings us an epoch that people can access the information or support they need instantaneously. Online Health Communities (OHCs), as a product of modern Internet, are convenient sources of health-related information that allow users to interact with peers having similar concerns. However, as many other virtual communities, OHCs face many challenges such as low user activity levels and high rates of turnover. Thus, it is important to understand the factors that influence users’ engagement in OHCs.

This study analyzed data from a public OHC that deals with breast cancer. Various computational methods made it possible to determine the type(s) of social support existing in each post. By summarizing and analyzing users’ seeking and receiving behaviors, I was able to understand how users interact and involve within this OHC. For example, users often joined the community because something sparked their interest, maybe an online article or the diagnosis of a family member. As they sought and received different types of social support, connected with various people or became embedded within different groups, their interests changed over time. Some of users used the site for a very short period, then left, while others were more active and engaged over longer periods.

This study aims at detecting factors that impact users’ engagements in OHCs. Its findings have implications for managing and sustaining stable OHCs, such as providing OHC managers with suggestions in improving website design and adopting interventions to motivate user contributions and retain users in the community.

Keywords

online health community, social support, user engagement

Pages

xi, 122 pages

Bibliography

Includes bibliographical references (pages 99-122).

Copyright

Copyright © 2017 Xi Wang

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