Deep Learning and Natural Language Processing to Detect Misinformation
Presenter(s)
Ian M. Cannon, David Fan
Files
Description
Misinformation is the act of spreading incorrect or false information about a given topic. With the upcoming presidential campaign, COVID-19, and other major events ongoing it is especially important to identify sources of misinformation. Our group proposes a novel method of classifying articles by using context and content indicators to debunk news articles containing misinformation. Most models take in articles and determine whether it is fake or not. We propose a method to predict content indicators to that highlight the credibility of an article and then decide if it is real or fake. This gives some agency to the reviewer by allowing one to see what were the major factors in deciding if an article is fake or not.
Publication Date
4-22-2020
Project Designation
Course Project
Primary Advisor
Saeedeh Shekarpour
Primary Advisor's Department
Computer Science
Keywords
Stander Symposium project, College of Arts and Sciences
United Nations Sustainable Development Goals
Peace, Justice, and Strong Institutions; Quality Education
Recommended Citation
"Deep Learning and Natural Language Processing to Detect Misinformation" (2020). Stander Symposium Projects. 1909.
https://ecommons.udayton.edu/stander_posters/1909
Comments
This project reflects research conducted as part of a course project designed to give students experience in the research process. Course: CPS 592 14