Parvez, Mohammad ZavidKabir, AshadAkhond, Mostafijur RahmanShondhy, Sumaiya IslamKhan, Forhad AhmedIbrahim, Syed ShoaibBarua, Shuvajit2021-10-192021-10-1920212021-01ID 17101532ID 17301083ID 17301144ID 17301168http://hdl.handle.net/10361/15432Cataloged from PDF version of thesis.Includes bibliographical references (pages 55-56).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.In 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.56 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.COVID-19Fake news detectionDatasetnews articleCOVID-19 (Disease)Thesis