Fake news detection on social media using stance detection

dc.contributor.author	Ahmed Usama Subhani, 01-134152-003
dc.contributor.author	Ahsan Maqbool, 01-134152-036
dc.date.accessioned	2020-08-16T05:08:39Z
dc.date.available	2020-08-16T05:08:39Z
dc.date.issued	2019
dc.identifier.uri	http://hdl.handle.net/123456789/9571
dc.description	Supervised by Ms. Momina Moetesum	en_US
dc.description.abstract	Fake news, spread through social media, pose a serious threat to our society. Identifying fake news is a complicated task. The first step leading to an automated fake news detection system is stance detection i.e. the relevance between headline and the body of an article. Stance detection can help in identifying click-bait headlines with unrelated body text(a technique mostly used by fake news distributors) and in evaluating the stance different news sources take towards a claim. In this project, we design and develop a system to detect stance between two bodies of text using Natural Language Processing techniques	en_US
dc.language.iso	en	en_US
dc.publisher	Bahria University Islamabad Campus	en_US
dc.relation.ispartofseries	BS (CS);P-8494
dc.subject	Computer Science	en_US
dc.title	Fake news detection on social media using stance detection	en_US
dc.type	Project Reports	en_US