Date of Award

May 2021

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Information Studies

First Advisor

Jin Zhang

Committee Members

Iris Xie, Xiangming Mu, Min Sook Park, Hengyi Fu

Keywords

health consumers, MedlinePlus, mental health, social network analysis, subject directory

Abstract

The Internet is a common means for people to search for health information. The subject directory of MedlinePlus offers Internet searchers a browsing environment so that those seekers could start from a broad term and refine their search terms to meet their real information needs, thus resulting in a better information search. For those novice users who are not familiar with relevant domain knowledge, MedlinePlus’s directory can be of great assistance and enable the portal to adopt to a more general population. Such a subject directory system and its involved health topics in the MedlinePlus portal formed a network where a specific research methodology, social network analysis, is applicable. In this study, four health topic groups – mental health, children, teenagers, and older adults - were selected as the focus for the investigation toward the subject directory on the MedlinePlus portal. This study applied social network analysis to explore the health topic directories and connection patterns among the health topics that comprised the subject directory of the MedlinePlus portal, and identified the influential topics (i.e., those health topics which play more important roles than others in connecting different topics) among the topic networks. As a result, different recommendations were made toward mental health, children, teenagers, and older adults related health topics, respectively. New optimized structural networks were suggested to be built for each of the four health topic subcategories according to the similarity values calculated through the cosine similarity measure in terms of the textual information contained in health topics’ Web pages, as well as the key nodes identified in the networks of health topics. Evaluations were later conducted to compare the original and optimized structural networks of the four health topic groups regarding their topics’ new similarity values. Newly identified influential health topics were verified to have improved the overall semantic connections among the whole networks. Last but not least, the recommendation results were evaluated by two health field experts and the evaluation outcomes proved that the recommendations suggested in this study were consistent with the opinions generated by health professionals. The findings of this research will provide suggestions to optimize and enhance the current navigation guidance system in MedlinePlus, improve the information searching effectiveness among the portal users, offer insights to public health portal creators, and support other researchers focusing on subject directory systems.

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