Althabiti, S. orcid.org/0000-0002-4646-0577, Alsalka, M.A. and Atwell, E. (Cover date: March 2023) A Survey: Datasets and Methods for Arabic Fake News Detection. International Journal on Islamic Applications in Computer Science And Technology, 11 (1). pp. 19-28. ISSN 2289-4012
Abstract
Social media's fast-growing popularity and convenient approval of unknown accounts have promoted an environment where unidentified users can act maliciously, for instance, by spreading fake news. Even though these social networks have been motivating researchers to deter such occurrences, they have not overcome this dilemma due to the immense volume of posted messages that require processing. One of the essential solutions to detect fake news is to measure the credibility of users based on various features and how a particular message was circulated. This paper surveys studies on false news detection, specifically in Arabic, including current datasets and used methods.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | Arabic Fake news; Arabic datasets; Arabic Survey; Survey; Fake News Detection; Misinformation; FND Methods |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Feb 2024 12:25 |
Last Modified: | 29 Feb 2024 12:25 |
Published Version: | http://www.sign-ific-ance.co.uk/index.php/IJASAT/a... |
Status: | Published |
Publisher: | Design for Scientific Renaissance |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:203420 |