Cargando…
An intelligent cybersecurity system for detecting fake news in social media websites
People worldwide suffer from fake news in many life aspects, healthcare, transportation, education, economics, and many others. Therefore, many researchers have considered seeking techniques for automatically detecting fake news in the last decade. The most popular news agencies use e-publishing on...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021563/ https://www.ncbi.nlm.nih.gov/pubmed/35469124 http://dx.doi.org/10.1007/s00500-022-07080-1 |
_version_ | 1784689861576359936 |
---|---|
author | Mughaid, Ala Al-Zu’bi, Shadi AL Arjan, Ahmed AL-Amrat, Rula Alajmi, Rathaa Zitar, Raed Abu Abualigah, Laith |
author_facet | Mughaid, Ala Al-Zu’bi, Shadi AL Arjan, Ahmed AL-Amrat, Rula Alajmi, Rathaa Zitar, Raed Abu Abualigah, Laith |
author_sort | Mughaid, Ala |
collection | PubMed |
description | People worldwide suffer from fake news in many life aspects, healthcare, transportation, education, economics, and many others. Therefore, many researchers have considered seeking techniques for automatically detecting fake news in the last decade. The most popular news agencies use e-publishing on their websites; even websites can publish any news they want. However, thus before quotation any news from a website, there should be a close look at news resource ranking by using a trusted websites classifier, such as the website world rank, which reflects the repute of these websites. This paper uses the world rank of news websites as the main factor of news accuracy by using two widespread and trusted websites ranking. Moreover, a secondary factor is proposed to compute the news accuracy similarity by comparing the current news with fakes news and getting the possible news accuracy. Experiments results are conducted on several benchmark datasets. The results showed that the proposed method got promising results compared to other comparative methods in defining the news accuracy. |
format | Online Article Text |
id | pubmed-9021563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-90215632022-04-21 An intelligent cybersecurity system for detecting fake news in social media websites Mughaid, Ala Al-Zu’bi, Shadi AL Arjan, Ahmed AL-Amrat, Rula Alajmi, Rathaa Zitar, Raed Abu Abualigah, Laith Soft comput Data Analytics and Machine Learning People worldwide suffer from fake news in many life aspects, healthcare, transportation, education, economics, and many others. Therefore, many researchers have considered seeking techniques for automatically detecting fake news in the last decade. The most popular news agencies use e-publishing on their websites; even websites can publish any news they want. However, thus before quotation any news from a website, there should be a close look at news resource ranking by using a trusted websites classifier, such as the website world rank, which reflects the repute of these websites. This paper uses the world rank of news websites as the main factor of news accuracy by using two widespread and trusted websites ranking. Moreover, a secondary factor is proposed to compute the news accuracy similarity by comparing the current news with fakes news and getting the possible news accuracy. Experiments results are conducted on several benchmark datasets. The results showed that the proposed method got promising results compared to other comparative methods in defining the news accuracy. Springer Berlin Heidelberg 2022-04-21 2022 /pmc/articles/PMC9021563/ /pubmed/35469124 http://dx.doi.org/10.1007/s00500-022-07080-1 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Data Analytics and Machine Learning Mughaid, Ala Al-Zu’bi, Shadi AL Arjan, Ahmed AL-Amrat, Rula Alajmi, Rathaa Zitar, Raed Abu Abualigah, Laith An intelligent cybersecurity system for detecting fake news in social media websites |
title | An intelligent cybersecurity system for detecting fake news in social media websites |
title_full | An intelligent cybersecurity system for detecting fake news in social media websites |
title_fullStr | An intelligent cybersecurity system for detecting fake news in social media websites |
title_full_unstemmed | An intelligent cybersecurity system for detecting fake news in social media websites |
title_short | An intelligent cybersecurity system for detecting fake news in social media websites |
title_sort | intelligent cybersecurity system for detecting fake news in social media websites |
topic | Data Analytics and Machine Learning |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021563/ https://www.ncbi.nlm.nih.gov/pubmed/35469124 http://dx.doi.org/10.1007/s00500-022-07080-1 |
work_keys_str_mv | AT mughaidala anintelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT alzubishadi anintelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT alarjanahmed anintelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT alamratrula anintelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT alajmirathaa anintelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT zitarraedabu anintelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT abualigahlaith anintelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT mughaidala intelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT alzubishadi intelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT alarjanahmed intelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT alamratrula intelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT alajmirathaa intelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT zitarraedabu intelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites AT abualigahlaith intelligentcybersecuritysystemfordetectingfakenewsinsocialmediawebsites |