Fake News Detection Using Machine Learning and Deep Learning Techniques

dc.contributor.authorBabi, Chaima
dc.contributor.authorSupervisor: Gadri, Said
dc.date.accessioned2023-07-09T09:41:23Z
dc.date.available2023-07-09T09:41:23Z
dc.date.issued2023-06-10
dc.description.abstractDetecting fake news has become a critical challenge in the digital era, where information spreads rapidly through various online platforms. This work focuses on the development and application of machine learning and deep learning techniques and develops a recurrent neural network (RNN)-based fake news detection model. The goal of this model is to accurately identify and classify fake news. Through our experimental work, we have demonstrated the high effectiveness and accuracy of this model in distinguishing fake news from genuine information.en_US
dc.identifier.urihttps://repository.univ-msila.dz/handle/123456789/40105
dc.language.isoenen_US
dc.publisherUniversity of M'silaen_US
dc.subjectFake News Detection, Deep Learning, Machine Learning, Artificial Neural Networks, Recurrent Neural Network.en_US
dc.titleFake News Detection Using Machine Learning and Deep Learning Techniquesen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Thesis_Chaima_Babi.pdf
Size:
1.71 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:

Collections