Deep Learning and Natural Language Processing to Detect Misinformation

Title

Deep Learning and Natural Language Processing to Detect Misinformation

Authors

Presenter(s)

Ian M. Cannon, David Fan

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

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 Posters, College of Arts and Sciences

United Nations Sustainable Development Goals

Peace, Justice, and Strong Institutions; Quality Education

Deep Learning and Natural Language Processing to Detect Misinformation

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