dc.contributor.advisor | Jahan, Sifat E | |
dc.contributor.advisor | Rasel, Annajiat Alim | |
dc.contributor.author | Hossain, Farhan | |
dc.contributor.author | Hasan, Md Zahid | |
dc.contributor.author | Hasan, Sourov | |
dc.contributor.author | Alam, Mobassherul | |
dc.contributor.author | Shahana, Afrin | |
dc.date.accessioned | 2023-10-15T05:01:03Z | |
dc.date.available | 2023-10-15T05:01:03Z | |
dc.date.copyright | ©2022 | |
dc.date.issued | 2022-05-29 | |
dc.identifier.other | ID 17101484 | |
dc.identifier.other | ID 17201060 | |
dc.identifier.other | ID 17301091 | |
dc.identifier.other | ID 17301135 | |
dc.identifier.other | ID 19201120 | |
dc.identifier.uri | http://hdl.handle.net/10361/21806 | |
dc.description | This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. | en_US |
dc.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 23-24). | |
dc.description.abstract | The expansion of the Internet and swift adoption of social media platforms such as Facebook, Twitter, Instagram, Reddit, etc., has seen news and information publicized in such a way that has never been perceived in human history before. This easy access to information has resulted in an exponential increase in the misleading and falsification of news. News articles with no valid source get circulated within a society causing chaos and confusion. This work examines existing techniques and technologies used to detect fake news and demonstrates a model that sees fake news using machine learning algorithms and evaluates its performance on real-world datasets. | en_US |
dc.description.statementofresponsibility | Farhan Hossain | |
dc.description.statementofresponsibility | Md Zahid Hasan | |
dc.description.statementofresponsibility | Sourov Hasan | |
dc.description.statementofresponsibility | Mobassherul Alam | |
dc.description.statementofresponsibility | Afrin Shahana | |
dc.format.extent | 34 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | Brac 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. | |
dc.subject | Covid-19 | en_US |
dc.subject | Fake Covid-19 news | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Classifiers | en_US |
dc.subject | Datasets | en_US |
dc.subject.lcsh | Epidemics | |
dc.subject.lcsh | Disinformation | |
dc.title | Detecting fake news on Covid-19 using machine learning algorithms | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |