Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/21695
DC FieldValueLanguage
dc.contributor.advisorDe, Rahul
dc.contributor.authorRoy, Arika
dc.contributor.authorBoga, Mona Rishi
dc.date.accessioned2022-10-26T12:25:16Z-
dc.date.available2022-10-26T12:25:16Z-
dc.date.issued2021
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/21695-
dc.description.abstractFake news is a fairly common phenomenon in the information and media landscape. It plays an active role in confirming the reader's beliefs and existing biases. From social media sites to news forums and blogs, the distinction between genuine and fake information is quietly blurring. Machine learning has taken a few strides in developing solutions that would distinguish between them. In our project, we would be utilizing large language models in natural language processing to study the distinctive features of fake news. The study would include the analysis of different types of fake news and the forms of fact altering mechanisms. We would be reviewing the existing detection models and disintegrating the aspects of fabricated news into identifying features. We would also be taking a few examples of fake news and testing the various approaches to establishing the veracity of the dataset.
dc.publisherIndian Institute of Management Bangalore
dc.relation.ispartofseriesPGP_CCS_P21_188
dc.subjectFake news
dc.subjectFact altering mechanisms
dc.subjectMedia industry
dc.subjectMedia landscape
dc.titleAnalysis of different types of fake news and the forms of fact altering mechanisms
dc.typeCCS Project Report-PGP
dc.pages15p.
Appears in Collections:2021
Files in This Item:
File SizeFormat 
PGP_CCS_P21_188.pdf5.57 MBAdobe PDFView/Open    Request a copy
Show simple item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.