| dc.contributor.author | Gurmeet | |
| dc.description.abstract | The 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.publisher | North Dakota State University | en_US |
| dc.rights | NDSU policy 190.6.2 | en_US |
| dc.title | Role of Bias in Information Warfare: Classifying Fake News Articles Using Natural Language Processing | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2020-09-04T19:38:24Z | |
| dc.date.available | 2020-09-04T19:38:24Z | |
| dc.date.issued | 2020 | |
| dc.identifier.uri | https://hdl.handle.net/10365/31527 | |
| dc.subject.lcsh | Fake news. | |
| dc.subject.lcsh | Mass media -- Objectivity. | |
| dc.subject.lcsh | Mass media and public opinion. | |
| dc.subject.lcsh | Natural language processing (Computer science) | |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | en_US |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Engineering | en_US |
| ndsu.department | Computer Science | en_US |
| ndsu.program | Software Engineering | en_US |
| ndsu.advisor | Straub, Jeremy | |
