Publication Date
2020
Document Type
Dissertation/Thesis
First Advisor
Alhoori, Hamed
Degree Name
M.S. (Master of Science)
Legacy Department
Department of Computer Science
Abstract
Scientific research is being increasingly shared online in a way such that there is a need to develop methodologies to measure the impact of specific papers in ways that go beyond traditional indicators of scholarly citations and beyond the scholarly community. In this thesis, new machine learning models are developed to measure and predict the impact ofresearch in the online context. The extent to which research papers are mentioned on social media platforms, i.e., their online sustainability, indicates the public's interest in and perhaps even the level of understanding of scientific topics. A research paper having a long lifespan, i.e., numerous mentions that continue over time, may constitute a significant scholarly and/or societal impact, depending on the context, and may lead to further impact in one or both of these contexts. For this purpose, machine learning models were developed to predict the online lifespan of given research articles and to identify the platforms that are most important to their long-term online impact. In addition, the emotional responses to the scientific outcomes shared online are investigated: machine learning models are built to predict the sentiment a given research article is most likely to elicit in tweets and Facebook posts. Based on the results, researchers will be better able to identify the potential emotional outcomes of their work and anticipate possible reactions and effects before submitting their research proposals and manuscripts for peer review and before posting their research outcomes online.
Recommended Citation
Syed, Mohammed Murtuza Shahzad, "Development of Machine Learning Models to Predict The online Impact of Research" (2020). Graduate Research Theses & Dissertations. 7713.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/7713
Extent
110 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
