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Ranking Systems For Fake News Detection

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International Hellenic University   

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Institutional Repository of the International Hellenic University   

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Ranking Systems For Fake News Detection (EN)
Velonis, Aristeidis (EN)
Peristeras, Vasileios (EL)
Stavrinides, Stavros (EN)
masterThesis
2022-01-07
2022-09-15
2022-09-15T07:31:07Z
In this thesis we analyze the ranking systems for fake news detec- tion. The dissertation is divided into 2 parts. In the theoretical and in the analysis of various models (FakerFact, Index, CSI, FNED) for de- tecting false news. In the theoretical part some definitions are men- tioned in order to make the subject more understandable, some im- portant events with fake news (2016 US Elections, 2017 French Elec- tions, 2020 Covid - 19) and finally an analysis is made for the EU, for the principles and values and how responded to the fake news chal- lenge. As far as the technical part, there is a lot of discussion in the literature about machine learning in fake news detection and in the latest models it seems to be taken into account. The article concludes that fake news can have devastating consequences for health and electoral issues. Also, no articles were found in the literature that combine something technical with something more theoretical, which means that the two sides may not communicate properly with each other. (EN)
ranking systems (EN)
Fake news (EN)
Αγγλική γλώσσα
School of Science and Technology, MSc in e-Business and Digital Marketing
School of Science and Technology, Master of Science (MSc) in Information and Communication Systems (EN)
Default License
International Hellenic University
Institutional Repository of the International Hellenic University
University Center of International Programmes of Studies (UCIPS)
Master Theses



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