Machine Learning Approach to Detect Fake News, Misinformation in COVID-19 Pandemic
Document Type
Conference Proceeding
Publication Date
6-9-2021
Abstract
Fake news is false information about current events, intentionally created to mislead readers. The spread of such fake news has the potential to create a negative impact on individuals and society. With today's straightforward creation of social media posts, there has been an increasing amount of fake news, compared to traditional media in the past. We present one of the most serious societal issue of misinformation, specifically using Presidential Election and COVID-19 health related fake news. We present multi-dimensional approaches that organizations and individuals could utilize for detecting fake news, ranging from human/social approaches, to technical approaches to organizational trust/policy approaches. The Machine Learning approach as a technical solution is presented for automating the detection of fake news and misleading contents. A fake news detection web application is presented to make it easy for end users to determine whether an article is legitimate or fake.
Identifier
85108141589 (Scopus)
ISBN
[9781450384926]
Publication Title
ACM International Conference Proceeding Series
External Full Text Location
https://doi.org/10.1145/3463677.3463762
First Page
575
Last Page
578
Grant
1747728
Fund Ref
National Science Foundation
Recommended Citation
Bojjireddy, Sirisha; Chun, Soon Ae; and Geller, James, "Machine Learning Approach to Detect Fake News, Misinformation in COVID-19 Pandemic" (2021). Faculty Publications. 4043.
https://digitalcommons.njit.edu/fac_pubs/4043
