Publication Date
2022
Document Type
Dissertation/Thesis
First Advisor
Alhoori, Hamed
Degree Name
M.S. (Master of Science)
Legacy Department
Department of Computer Science
Abstract
Research and development have always initiated innovation and breakthroughs in technology. These technological advancements in recent years have provided a global medium for research to be disseminated through online platforms. These web-based platforms and the interactions that take place on them affect the dissemination, impact, and perception of online information. This thesis investigates the broader impact of science and health using social media posts, online patents, videos, and images by building machine learning and topic models. First, this study predicts patent citations to scientific research and identifies important factors essential to economic impact. We found that the citation of research in patents is a strong indicator of economic impact and strengthens the popularity of scholarly research. Second, we studied video communication of scholarly research and found that it has been increasing and there is a lack of studies in this area. Therefore, this study bridges the gap between scientific videos and research by building models to predict videos’ scholarly and societal impact. Finally, this study aims to understand the impact of health-related topics on the public. Instagram images with textual features express different views on topics from users’ perspectives worldwide. We built topic models on the posts related to health and COVID-19 to analyze users' perceptions across different locations. The thesis identifies factors essential in recognizing the broader influence of science and health. Based on the results, we will have a better understanding of the economic and societal impact of science and the public understanding of health.
Recommended Citation
Shaikh, Abdul Rahman, "Modeling The Broader Impact of Science and Health Using Social Media" (2022). Graduate Research Theses & Dissertations. 7656.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/7656
Extent
112 pages
Language
eng
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
