[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122686-en":3,"doc-seo-122686-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122686,962075006959,"Anda","https://ap-avatar.wpscdn.com/avatar/e0002397efbe92a78e?_k=1776741047341049297",8,"Research & Report","News’ Credibility Detection on Social Media Using Machine Learning Algorithms - Article 2","Social media enables rapid, free access to news, but it also accelerates the spread of misleading, low-quality, incorrect, and fake information. False news can harm personal reputation and erode public trust, making credibility detection critical. This research proposes a model for detecting the credibility of Arabic news from social media, focusing on Arabic tweets about the COVID-19 pandemic. The approach applies text mining and a decision tree classifier, achieving the best accuracy of 86.6%.","Future Computing and Informatics Journal  \n\n| Volume 8\u003Cbr>Issue 1 (2023) Volume 8 Issue 1 | Article 2 |\n| --- | --- |\n| News’Credibility Detection on Social Media Using Machine Learning Algorithms\u003Cbr>Farah Yasser\u003Cbr>Business Information Systems, Faculty of Commerce and Business Administration, Helwan University, Egypt, [farah.yasser21@commerce.helwan.edu.eg](farah.yasser21@commerce.helwan.edu.eg)\u003Cbr>Sayed AbdelMawgoud\u003Cbr>Information Systems Department, Helwan University, Egypt, [sgaber14@gmail.com](sgaber14@gmail.com)\u003Cbr>[Amira M. Idrees AMI](Amira M. Idrees AMI)\u003Cbr>Future University in Egypt, [amira.mohamed@fue.edu.eg](amira.mohamed@fue.edu.eg)\u003Cbr>Follow this and additional works at: [https://digitalcommons.aaru.edu.jo/fcij](https://digitalcommons.aaru.edu.jo/fcij)\u003Cbr> Part of the Computer and Systems Architecture Commons, and the Data Storage Systems Commons |  |\n\nRecommended Citation  \nYasser, Farah; AbdelMawgoud, Sayed; and Idrees, Amira M. AMI () \"News’ Credibility Detection on Social Media Using Machine Learning Algorithms,\" Future Computing and Informatics Journal: Vol. 8: Iss. 1, Article 2.  \nAvailable at: [https://digitalcommons.aaru.edu.jo/fcij/vol8/iss1/2](https://digitalcommons.aaru.edu.jo/fcij/vol8/iss1/2)  \nThis Article is brought to you for free and open access by Arab Journals Platform. It has been accepted for inclusion in Future Computing and Informatics Journal by an authorized editor. The journal is hosted on Digital Commons, an Elsevier platform. For more information, please contact [rakan@aaru.edu.jo](rakan@aaru.edu.jo), [marah@aaru.edu.jo](marah@aaru.edu.jo),  \n[u.murad@aaru.edu.jo](u.murad@aaru.edu.jo).  \nFuture Computing and Informatics Journal Homepage: [https://digitalcommons.aaru.edu.jo/fcij/](https://digitalcommons.aaru.edu.jo/fcij/)[ ](https://digitalcommons.aaru.edu.jo/fcij/)doi: [http://Doi.org/10.54623/fue.fcij.8.1.2](http://Doi.org/10.54623/fue.fcij.8.1.2)  \nNews’ Credibility Detection on Social Media Using Machine Learning Algorithms  \nFarah Yasser  \nBusiness Information Systems, Faculty of Commerce and Business Administration, Helwan University, Egypt  \n[farah.yasser21@commerce.helwan.edu.eg](farah.yasser21@commerce.helwan.edu.eg)  \nSayed AbdelGaber AbdelMawgoud  \nInformation Systems Department, Helwan University, Egypt  \n[sgaber14@gmail.com](sgaber14@gmail.com)  \nAmira M. Idrees  \nFaculty of Computers and Information Technology,  \nFuture University in Egypt, Egypt  \n[amira.mohamed@fue.edu.eg](amira.mohamed@fue.edu.eg)  \nAbstract  \nSocial media is essential in many aspects of our lives. Social media allows us to find news for free. anyone can access it easily at any time. However, social media may also facilitate the rapid spread of misleading news. As a result, there is a probability that low-quality news, including incorrect and fake information, will spread over social media. As well as detecting news credibility on social media becomes essential because fake news can affect society negatively, and the spread of false news has a considerable impact on personal reputation and public trust. In this research, we conducted a model that detects the credibility of Arabic news from social media; particularly Arabic tweets. The content of the tweets revolves around the COVID-19 pandemic. The proposed model applied to detect news credibility using text mining techniques and one of the well-known machine learning classifiers, Decision tree which has the best accuracy equal to 86.6% .  \nKeywords: social media, news credibility, text mining, and machine learning.  \n21  \n1.Introduction  \nSocial networking sites has become a platform for spreading news and information between people over the world very fast, the progress of Users'interactions with others through social media have considerably risen as a result of social networking sites. it is true that the business sector now takes social networking seriously, the spreading of news via social media which has significantly impacted both people and busi","cbCaiceT4qxvnRMX","https://ap.wps.com/l/cbCaiceT4qxvnRMX","pdf",733631,1,12,"English","en",105,"# Introduction\n# Related Works\n# Proposed Methodology\n# Experimental Study\n# Conclusions","[{\"question\":\"Why is detecting news credibility on social media important?\",\"answer\":\"Social media spreads information quickly, making it difficult to distinguish credible from noncredible news. Fake news can negatively affect society by damaging personal reputation and reducing public trust.\"},{\"question\":\"What type of data and language does the proposed model analyze?\",\"answer\":\"The model analyzes Arabic news content from social media, specifically focusing on Arabic tweets related to the COVID-19 pandemic.\"},{\"question\":\"Which techniques and classifier are used to detect credibility, and what accuracy is achieved?\",\"answer\":\"The method uses text mining techniques and applies a decision tree machine learning classifier. It reports the best accuracy of 86.6%.\"}]","News’ Credibility Detection on Social Media Using Machine Learning Algorithms - Article 2 | PDF",1785812186,30,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"news-credibility-detection-on-social-media-using-machine-learning-algorithms-article-2","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/news-credibility-detection-on-social-media-using-machine-learning-algorithms-article-2/122686/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is detecting news credibility on social media important?","Question",{"text":75,"@type":76},"Social media spreads information quickly, making it difficult to distinguish credible from noncredible news. Fake news can negatively affect society by damaging personal reputation and reducing public trust.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What type of data and language does the proposed model analyze?",{"text":80,"@type":76},"The model analyzes Arabic news content from social media, specifically focusing on Arabic tweets related to the COVID-19 pandemic.",{"name":82,"@type":73,"acceptedAnswer":83},"Which techniques and classifier are used to detect credibility, and what accuracy is achieved?",{"text":84,"@type":76},"The method uses text mining techniques and applies a decision tree machine learning classifier. 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