Date of Award

May 2024

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Information Studies

First Advisor

Jin Zhang

Committee Members

Laretta Henderson, Xiangming S Mu, Min S Park

Keywords

healthcare, Information Retrieval, Malaria, Malaria Africa, Social media, YouTube

Abstract

Due to the proliferation of the use of social media, the public—especially patients and their family or friends, try to seek answers from resources such as Facebook, Yahoo! Answers, YouTube, MedlinePlus, and other sites. This research study centered on investigating characteristics and the relationship between users’ online patterns while using and posting information on YouTube related to health-care—in this case malaria (a life-threatening mosquito-borne blood disease). This research study applied a mixed-methods approach. Subject analysis, multi-dimensional scaling (MDS) analysis, inferential analysis, and temporal analysis methods were employed to analyze and investigate users’ health information posts on YouTube in Africa. This information from social media revealed subject patterns not easily exposed from health institutions’ reports. 10 distinct categories were identified using subject analysis: 1. fight against malaria, 2. Government policy on malaria, 3. cause and effects of malaria, 4. methods of prevention, 5. treatment of malaria, 6. malaria pandemic, 7. campaign and awareness, 8. community efforts, 9. testing and trial, and 10. research. Research findings of this study further revealed that there was significant difference among Four periods (January – March = Period 1; April – June= Period 2; July – September = Period 3; October– December = Period 4), and 10 categories in terms of malaria-related records on YouTube. Unique keywords were added and disappearing keywords were discovered. Likes, and users’ views among the four periods were identified. The study discovered that category 9 (testing and trial) in Period 1 emerged as the one with highest unique keywords, Category 3 (cause and effects of malaria) in Period 4 had the most keywords disappeared, Category 3 in Period 1 had the highest number of added keywords, Category 7 (malaria pandemic) in Period 4 had the highest number of users’ likes, and Category 9 in Period 3 had the highest users’ views. These findings have theoretical, practical, and methodological implications towards the betterment of malaria-related websites’ internal search and flow of information to all end-users. Theoretically this research filled the gap in the field by studying malaria related post on YouTube. Practically, the discovered 10 categories, and related keywords can be used as subject guidance in malaria-related portals and to improve the internal search engines. The methodology used in this study can be applied to investigating and exploring social media content in other social media platforms focusing on malaria and other related healthcare topics.

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