An innovative approach for fake news detection using machine learning

Maya Hisham, Raza Hasan, Saqib Hussain

Research output: Contribution to journalArticlepeer-review


This research aims to increase people's awareness of fake news on online social networks and help them determine the reliability of information they consume. It investigates methods for detecting fake news sources, authors, and subjects on online social networks. The project uses an open-source online dataset of fake and real news to determine the credibility of news. Various text feature extraction techniques and classification algorithms are reviewed, with the Support Vector Machine (SVM) linear classification algorithm using TF-IDF feature extraction achieving the highest accuracy of 99.36%. Random Forest (RF) and Naive Bayes (NB) had accuracy scores of 98.25% and 94.74%, respectively.
Original languageEnglish
Pages (from-to)115-124
Number of pages10
JournalSir Syed University Research Journal of Engineering & Technology
Issue number1
Publication statusPublished - 28 Jun 2023

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