Online fake news detection algorithm
Microblogging sites allowing disseminating distasteful content. This has become vigorous and nearly unstoppable now. Spreading online fake news has been identified as one of the major top concern of online abuse. Due to the difficulty in preventing and evaluating what does fake news contain prior...
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iium-584462018-05-17T06:43:07Z http://irep.iium.edu.my/58446/ Online fake news detection algorithm Sirajudeen, Sakeena M A. Azmi, Nur Fatihah Abubakar, Adamu Q350 Information theory Microblogging sites allowing disseminating distasteful content. This has become vigorous and nearly unstoppable now. Spreading online fake news has been identified as one of the major top concern of online abuse. Due to the difficulty in preventing and evaluating what does fake news contain prior to publishing it online, if an algorithm is known for detecting fake news, then spreading online fake news wouldn’t exist in the first place, lead this paper to presents an evaluation of the effectiveness of algorithm(s), able to detect and filter to reasonable degree of accuracy what constitute an online fake news. The proposed approach is a multi-layered evaluations technique to be built as an app, where all information read online is associated with a tag, given a description of the facts about the contain. A proof of concept is provided for better understanding of the proposed techniques. This has contributed in providing possible steps to be taken by some popular Microblogging sites to stop the widespread of fake news. Journal of Theoretical and Applied Information Technology 2017-09-15 Article PeerReviewed application/pdf en http://irep.iium.edu.my/58446/1/Published.pdf application/pdf en http://irep.iium.edu.my/58446/7/Online%20fake%20news%20detection%20algorithm.pdf Sirajudeen, Sakeena M and A. Azmi, Nur Fatihah and Abubakar, Adamu (2017) Online fake news detection algorithm. Journal of Theoretical and Applied Information Technology, 95 (17). pp. 4114-4122. ISSN 1992-8645 E-ISSN 1817-3195 http://www.jatit.org/volumes/Vol95No17/7Vol95No17.pdf |
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Q350 Information theory Sirajudeen, Sakeena M A. Azmi, Nur Fatihah Abubakar, Adamu Online fake news detection algorithm |
description |
Microblogging sites allowing disseminating distasteful content. This has become vigorous and nearly
unstoppable now. Spreading online fake news has been identified as one of the major top concern of online
abuse. Due to the difficulty in preventing and evaluating what does fake news contain prior to publishing it
online, if an algorithm is known for detecting fake news, then spreading online fake news wouldn’t exist in
the first place, lead this paper to presents an evaluation of the effectiveness of algorithm(s), able to detect and filter to reasonable degree of accuracy what constitute an online fake news. The proposed approach is a multi-layered evaluations technique to be built as an app, where all information read online is associated
with a tag, given a description of the facts about the contain. A proof of concept is provided for better
understanding of the proposed techniques. This has contributed in providing possible steps to be taken by
some popular Microblogging sites to stop the widespread of fake news. |
format |
Article |
author |
Sirajudeen, Sakeena M A. Azmi, Nur Fatihah Abubakar, Adamu |
author_facet |
Sirajudeen, Sakeena M A. Azmi, Nur Fatihah Abubakar, Adamu |
author_sort |
Sirajudeen, Sakeena M |
title |
Online fake news detection algorithm |
title_short |
Online fake news detection algorithm |
title_full |
Online fake news detection algorithm |
title_fullStr |
Online fake news detection algorithm |
title_full_unstemmed |
Online fake news detection algorithm |
title_sort |
online fake news detection algorithm |
publisher |
Journal of Theoretical and Applied Information Technology |
publishDate |
2017 |
url |
http://irep.iium.edu.my/58446/ http://irep.iium.edu.my/58446/ http://irep.iium.edu.my/58446/1/Published.pdf http://irep.iium.edu.my/58446/7/Online%20fake%20news%20detection%20algorithm.pdf |
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2023-09-18T21:22:39Z |
last_indexed |
2023-09-18T21:22:39Z |
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1777411984272130048 |