FAKE NEWS DETECTION

dc.contributor.author	Shubham Bist, 18SCSE1010444
dc.date.accessioned	2022-07-29T09:27:08Z
dc.date.available	2022-07-29T09:27:08Z
dc.date.issued	2022-05
dc.identifier.uri	http://10.10.11.6/handle/1/9972
dc.description.abstract	Fake news has quickly become a society problem, being used to propagated false or rumour information in order to change people’s behaviour, this topic on social media has recently attracted tremendous attention. We are using the Naïve bays and passive aggressive classifier algorithm which can predict with an accuracy of roughly around 86%. This could help the novice project creator and could assist them in the planning for their crowd funding project. The future work in the project is that we might need to tune the model again as news in something which we couldn’t predict.	en_US
dc.language.iso	en	en_US
dc.publisher	Galgotias University	en_US
dc.subject	FAKE NEWS DETECTION	en_US
dc.subject	COMPUTER SCIENCE AND ENGINEERING	en_US
dc.title	FAKE NEWS DETECTION	en_US
dc.type	Other	en_US