Date of Award

Summer 2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Information Systems - (Ph.D.)

Department

Informatics

First Advisor

Songhua Xu

Second Advisor

Yi-Fang Brook Wu

Third Advisor

Michael Bieber

Fourth Advisor

Hai Nhat Phan

Fifth Advisor

L. C. Kaufman

Sixth Advisor

Reethi Narasimhan Iyengar

Abstract

The widespread and popular use of social media and social networking applications offer a promising opportunity for gaining knowledge and insights regarding population health conditions thanks to the diversity and abundance of online user-generated information (UGHI) relating to healthcare and well-being. However, users on social media and social networking sites often do not supply their complete demographic information, which greatly undermines the value of the aforementioned information for health 2.0 research, e.g., for discerning disparities across population groups in certain health conditions. To recover the missing user demographic information, existing methods observe a limited scope of user behaviors, such as word frequencies exhibited in a user’s messages, leading to sub-optimal results.

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