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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    COVID-19 related fake news detection model

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    17101532, 17301083, 17301144, 17301168_CSE.pdf (2.819Mb)
    Date
    2021-01
    Publisher
    Brac University
    Author
    Shondhy, Sumaiya Islam
    Khan, Forhad Ahmed
    Ibrahim, Syed Shoaib
    Barua, Shuvajit
    Metadata
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    URI
    http://hdl.handle.net/10361/15432
    Abstract
    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.
    Keywords
    COVID-19; Fake news detection; Dataset; news article
     
    LC Subject Headings
    COVID-19 (Disease)
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 55-56).
    Department
    Department of Computer Science and Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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