COVID-19 related fake news detection model

dc.contributor.advisorParvez, Mohammad Zavid
dc.contributor.advisorKabir, Ashad
dc.contributor.advisorAkhond, Mostafijur Rahman
dc.contributor.authorShondhy, Sumaiya Islam
dc.contributor.authorKhan, Forhad Ahmed
dc.contributor.authorIbrahim, Syed Shoaib
dc.contributor.authorBarua, Shuvajit
dc.date.accessioned2021-10-19T06:07:51Z
dc.date.available2021-10-19T06:07:51Z
dc.date.issued2021-01
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 55-56).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
dc.description.abstractIn this era of developed information and technology, any sort of information runs faster than air. The reliability of the information can be tricky at times. Some news publishing sources can publish news that are actually misguiding. The drastic evolution of electronic media over the past couple of decades has fueled the spread of fake news causing confusion and misunderstanding among the mass regarding any topic. The main motive behind producing these fake news is to create an agenda or to spread trepidation among people. People tend to become more panicked during any kind of disaster or pandemic, this it is easier to make them believe these misinformation in these times. Likewise, COVID-19 pandemic is not out of the grasp of misinformation spreading. To tackle this, we have proposed a Fake News Prediction model that will be used to detect fake news regarding COVID-19 that are being circulated in different electronic media.
dc.identifier.otherID 17101532
dc.identifier.otherID 17301083
dc.identifier.otherID 17301144
dc.identifier.otherID 17301168
dc.identifier.otherhttps://dspace.bracu.ac.bd/server/api/core/items/b91bf933-66d2-4a58-aaeb-9efcb51f3093
dc.identifier.urihttp://hdl.handle.net/10361/15432
dc.language.isoen
dc.publisherBRAC University
dc.sourceBRAC University Institutional Repository
dc.subjectCOVID-19
dc.subjectFake news detection
dc.subjectDataset
dc.subjectnews article
dc.titleCOVID-19 related fake news detection model
dc.typeThesis

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
17101532, 17301083, 17301144, 17301168_CSE.pdf
Size:
2.82 MB
Format:
Adobe Portable Document Format