Date of Award
5-2024
Culminating Project Type
Starred Paper
Styleguide
ieee
Degree Name
Computer Science: M.S.
Department
Computer Science and Information Technology
College
School of Science and Engineering
First Advisor
Dr. Maninder Singh
Second Advisor
Dr. Mark Petzold
Third Advisor
Dr. Jie H Meichsner
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Keywords and Subject Headings
Biomedical Information Extraction, MetaMap, ScispaCy, Fake News Detection, Deep Learning
Abstract
The COVID-19 pandemic has led to an unprecedented surge in disseminating accurate and false information across social media and online platforms. The spread of fake news about COVID-19 poses significant public health risks, including confusion, panic, and even fatalities. We propose a novel computational approach to address this urgent issue, by integrating advanced Natural Language Processing (NLP) algorithms like MetaMap and ScispaCy to extract biomedical information from news articles. Motivated by the necessity to combat misinformation, our study evaluates the performance of deep learning models, including Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), in detecting fake news. We observed that the ScispaCy in combination with LSTM model, leveraging domain-specific tools, achieved the highest performance across all evaluated metrics, with 87% accuracy, 90% precision, 86% recall, 88% F1-Score, and 87% AUC score compared to other models.
Recommended Citation
Khatiwada, Rabina, "A Novel Computational Approach for COVID-19 Fake News Detection by Utilizing Deep Learning Techniques" (2024). Culminating Projects in Computer Science and Information Technology. 51.
https://repository.stcloudstate.edu/csit_etds/51
Comments/Acknowledgements
I want to express my sincere gratitude to the St. Cloud State University computer science faculty for their consistent support and assistance during my academic journey. I am particularly grateful to Dr. Maninder Singh, my adviser, for his insightful aid and guidance, which was highly beneficial in completing my Starred Paper. I would like to sincerely thank Dr. Mark Petzold and Dr. Jie H Meichsner, members of my committee, for their invaluable contributions.
My profound gratitude goes out to Dr. Ibrahim Soumare, my supervisor at the Statistical Consulting Center, whose encouragement and mentorship have been pivotal in my personal growth and professional development.
Finally, I would like to express my heartfelt gratitude to my family and friends for their unwavering support and the nurturing environment they provided, enabling me to thrive. Their constant belief in my ability, even in times of difficulty, has been the basis of my accomplishments.