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dc.contributor.author
Chouliara, Vasiliki
el
dc.date.accessioned
2023-04-11T12:16:29Z
dc.date.available
2023-04-11T12:16:29Z
dc.date.issued
2023-04-11
dc.identifier.uri
https://repository.ihu.edu.gr//xmlui/handle/11544/30146
dc.rights
Default License
dc.subject
Text analytics
el
dc.subject
Machine learning
el
dc.subject
Deep learning
el
dc.subject
Fake news detection
el
dc.title
Fake News Detection
en
heal.type
masterThesis
en_US
heal.dateAvailable
2023-03-10
heal.language
en
en_US
heal.access
free
en_US
heal.license
http://creativecommons.org/licenses/by-nc/4.0
en_US
heal.recordProvider
School of Science and Technology, MSc in Data Science
en_US
heal.publicationDate
2023-01-27
heal.abstract
Easy and quick information diffusion on the web and especially in social media (i.e., Facebook, Twitter, etc.) has been rapidly proliferating during the past decades. As information is posted without any kind of verification of its veracity, fake news has become a problem of great influence in our information driven society. With the current rate of news generated in social media, the differentiation between real and fake news has become challenging. Thus, to mitigate the consequences of fake news and its propagation, considerable research has been conducted both by the academia and the industry, to create automated approaches to detect malicious content. A plethora of approaches have been investigated, most of which identify patterns on fake news after they are already disseminated. The need for early detection methods is crucial. The goal of this thesis is to review the current approaches for detecting disinformation and propose an effective framework that utilizes only the text features of the news, without using any other related metadata. Several Machine Learning models and Natural Language Processing techniques have been used during experimentation. The findings reveal that a combination of linguistic features and text-based word vector representations through ensemble methods can predict fake news with high accuracy.
el
heal.advisorName
Tjortjis, Christos
el
heal.committeeMemberName
Berberidis, Christos
en
heal.committeeMemberName
Koukaras, Paraskevas
el
heal.academicPublisher
IHU
el
heal.academicPublisherID
ihu
en_US


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