Role of Bias in Information Warfare: Classifying Fake News Articles Using Natural Language Processing

dc.contributor.authorGurmeet
dc.date.accessioned2020-09-04T19:38:24Z
dc.date.available2020-09-04T19:38:24Z
dc.date.issued2020
dc.description.abstractThe way that people consume news, entertainment and media has been changed. The print media and even television have started to become obsolete. In this digital age, social media being the biggest news source for the masses has become an issue in terms of security and the manipulation of facts. Add to this the fact that the content is catered towards the audience with respect to what suits the marketers. The consumer is no longer the dictator of what they want to consume but has become a product for the streaming services. The impact of targeted information propagation is huge and there is a need to study how we can maneuver it. In this paper we see the role that bias plays in an information perception model and how certain words and linguistic patterns can be used to determine if a source of news is authentic or not.en_US
dc.identifier.urihttps://hdl.handle.net/10365/31527
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
dc.subject.lcshFake news.
dc.subject.lcshMass media -- Objectivity.
dc.subject.lcshMass media and public opinion.
dc.subject.lcshNatural language processing (Computer science)
dc.titleRole of Bias in Information Warfare: Classifying Fake News Articles Using Natural Language Processingen_US
dc.typeMaster's paperen_US
ndsu.advisorStraub, Jeremy
ndsu.collegeEngineeringen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.departmentComputer Scienceen_US
ndsu.programSoftware Engineeringen_US

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