dc.contributor.author | Tusher, Shakib Ahmed | |
dc.contributor.author | Shawan, Md.Shameem Alam | |
dc.contributor.author | Akter, Mst.Farhana | |
dc.date.accessioned | 2022-09-04T05:10:42Z | |
dc.date.available | 2022-09-04T05:10:42Z | |
dc.date.issued | 2022-01-04 | |
dc.identifier.uri | http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/8530 | |
dc.description.abstract | Fake news detection is as important as cleaning crime from the society. In this digital era spreading violence and manipulating people deception towards an issue become very easy than ever. More and more authentic news are mutilated into fake news for some peoples own mean .In our day to day life we use many online platform for both entertainment and other uses .In those places we are continuously bombarded with fake news. This toxicity needs to be stop for our own good. And to stop the spreading of fake news, detecting it is the most inescapable part. Our research is based on that inescapable part. We tried to create a model for identifying fake news with a very big dataset of Bangla news data. All the data we have collected are from various online sources .Also we have used both machine and deep learning methods for our study. In machine learning method LR, SVM and RF shows 95% of highest accuracy .On the other hand in deep learning method LSTM and BERT give the best accuracy of 93%. Although we have used many methods but few methods we couldn’t use for our low performance device. However an application can be develop with this research to identify the news either fake or authentic. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Daffodil International University | en_US |
dc.subject | Fake news | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Deep learning | en_US |
dc.title | Bangla Fake News Detection Using Machine Learning and Deep Learning Methods | en_US |
dc.type | Article | en_US |