IJLLC | Supervised Machine Learning Applications for Detecting Internet Research Agency Misinformation

Indexing and Abstracting

Supervised Machine Learning Applications for Detecting Internet Research Agency Misinformation

Thomas Wiese , Jessica Wiese

International Journal of Language, Literature and Culture (IJLLC), Vol-3,Issue-1, January - February 2023, Pages 17-24, 10.22161/ijllc.3.1.3

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Article Info: Received: 17 Jan 2023, Received in revised form: 11 Feb 2023, Accepted: 19 Feb 2023, Available online: 28 Feb 2023

Abstract:

Misinformation has shifted political narratives across the globe. Because information shared over social media platforms lack traditional publishers and editors, the public is more susceptible to consuming information that is untrue. During the 2016 U.S. presidential election, the Russian government sponsored information operatives to spread misleading and/or false claims through social media. This study defines a method for automated detection of misinformation on social media using machine learning.

Keywords:

Information Security, Machine Learning, Artificial Intelligence, Misinformation, Fake News, Natural Language Processing, Data, Technology, Analytics, Warfare

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