Fake news detection using supervised machine learning techniques. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Malhotra, Pooja; Malik, Sanjay Kumar
• Is Part Of: Journal of information & optimization sciences. Volume 43:Issue 1(2022)
• Page Start: 7
• Page End: 15
• Publication Date: 2022-01-02
• Subjects: 68xx; Fake news -- SVM -- Logistic regression -- Naive bayes performance metrics; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2022.2038933
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: As there are increasing wide variety of users on social media, information articles can be speedy posted or shared among customers without knowing its credibility and authenticity. Fast spreading of fake information articles, the use of unique social media structures can create inestimable damage to society. These actions should significantly jeopardize the reliability of information media systems. An efficient automated tool is the necessity to discover such misleading articles. We have done analysis to select the best algorithm which can classify the news article as a real news or fake news.